# Aletyx Full Context > A consolidated, machine-readable corpus of Aletyx company, product, solution, service, pricing, author, topic, and editorial content for AI systems. Technical product documentation is maintained separately and is not duplicated here. Use the [Aletyx full documentation context](https://aletyx.ai/docs/llms-full.txt) for documentation, guides, and API reference material. Each document below comes from a public, indexable canonical page. The Source URL is authoritative, and documents are ordered by canonical URL. --- # AI-native decisions and workflows. Every outcome accountable. Source: https://aletyx.ai/ Governed decisions and workflows run your mission-critical operations. Aletyx makes them AI-native and accountable, whether you start new or modernize what already works. [Try AI Assistant free for 14 days](https://aletyx.ai/ai-assistant/) Watch a 2-minute overview > Our critical decisioning now runs on Aletyx within Plaisse, enabling us to continue modernizing our legacy Drools/BRMS infrastructure in weeks, without business disruption, and providing a scalable, AI-enabled foundation for our future decisioning capabilities. **Darshan Mehta** Managing Director, Application Development at Pennymac ![PennyMac](https://aletyx.ai/_astro/pennymac@4x.SpobuyG3_ZM4oW8.webp) ![JPMorgan Chase](https://aletyx.ai/_astro/jpmorgan-chase@4x.DZIm6utS_1CUvVT.webp) ![Dubai Islamic Bank](https://aletyx.ai/_astro/dib@4x.C-O2Jcnb_Z29jSFX.webp) ![Omron](https://aletyx.ai/_astro/omron@4x.DqK54iki_2nfWJF.webp) ![Aletyx Decision Control showing governed decisions, reviewed changes, and an AI assistant](https://aletyx.ai/_astro/aletyx-hero-final.CSwCsYLn_Rzp9o.webp) > “We spent nearly two decades contributing to this technology in open source, leading the product at Red Hat and IBM. We watched customers get forced into rewrites. We left to build what it was never allowed to be.” [Read our story](https://aletyx.ai/about-us/) AI for high-stakes operations ## Let AI assist. Keep execution governed. AI can interpret complex context across pricing, patient protocols, eligibility, and risk. Aletyx ensures every resulting action follows approved policy, runs reproducibly, and records why it happened. ### Policy controls action AI interprets the context. Approved decision logic determines what the system does. ### Outcomes stay reproducible Governed inputs, policy, and versions create results you can replay and verify. ### Every action is defensible Trace each outcome to its inputs, policy, version, and execution history. Meet Aletyx ## Governance built into every decision, workflow, and agent. Aletyx brings decision intelligence, process automation, agents, and production governance into one AI-native platform. Start new or bring the rules and workflows already running your business. Every change and outcome remains testable, reviewable, versioned, and traceable. ![Existing Drools DRL rules and a jBPM workflow preserved together in VS Code](https://aletyx.ai/_astro/aletyx-card-01-keep-what-works.CLqtYD0R_1GfcJN.webp) ### Keep what works Preserve existing rules and workflows while moving them onto a modern, AI-native foundation. ![Aletyx AI Assistant change request with a reviewable before-and-after decision diff](https://aletyx.ai/_astro/aletyx-card-02-ai-drafts-you-approve._HNT1HLE_Z2pa0GK.webp) ### AI edits. You review. Ask for changes in plain language, then inspect the exact diff before anything reaches production. ![Aletyx execution detail tracing model version, input data, and decision output](https://aletyx.ai/_astro/aletyx-card-04-trace-every-outcome.B0wyNqeK_Z462OM.webp) ### Trace every outcome Replay every decision, workflow step, and agent action with its inputs, version, and execution history. AI Assistant · Generally available ## Specialized AI for decision modeling. Create a complete model from a policy or spreadsheet. Update the model you already use with exact, reviewable edits. Generate tests to validate the outcome. [Explore AI Assistant](https://aletyx.ai/ai-assistant/) ![Aletyx AI Assistant showing coordinated model changes across a decision graph, change review, and decision table](https://aletyx.ai/_astro/aletyx-hero-final.CSwCsYLn_Z1rokWL.webp) Why enterprises choose Aletyx ## Build what’s next. Keep what already works. Start new with AI-native decisions and workflows, or modernize the systems already running your business. Aletyx gives both the same execution, governance, and traceability. [Try a guided pilot](https://aletyx.ai/free-trial/) ### AI native from the start Build decisions and workflows with AI embedded in authoring, execution, and operations. ### No forced rewrites Preserve existing logic and behavior while you modernize. ### A complete execution trail Review and replay every decision, workflow step, and agent action. ### Founding engineers Direct support from the engineers behind Drools, jBPM and Kogito. ### Predictable pricing Flat-fee pricing without usage surprises. Decision Intelligence & Intelligent Process Automation ## From policy to action, keep every decision and workflow under control. Decision Intelligence defines, executes, and governs business decisions. Intelligent Process Automation coordinates work across systems, people, and agents. Together, they carry approved policy through every decision and action, with the complete execution trail to prove it. Aletyx Decision Intelligence ### Decide: Turn policy into decisions you can run and defend Model, test, execute, and govern business decisions while agents reason with approved policy. - Start new or modernize existing decision logic without rewrites. - Let analysts and agents work with governed decision models. - Record every input, version, and outcome in a complete execution trail. [Explore Decision Intelligence](https://aletyx.ai/decision-intelligence/) Aletyx Intelligent Process Automation ### Coordinate: Systems, people, and agents without losing control Run end-to-end operations through workflows that carry approved policy across every system, human task, and agent action. - Start new or preserve existing workflow investments. - Coordinate agents natively inside business operations. - Keep every step governed, stateful, and traceable. [Explore Intelligent Process Automation](https://aletyx.ai/intelligent-process-automation/) Ready for real production environments ## Modernize the decisions and workflows you trust. Make them ready for AI. Start new on Aletyx or move existing Drools, jBPM, RHPAM, BAMOE, KIE Server, RHDM, and BRMS workloads without a rewrite. Preserve proven behavior and interfaces while adding AI-native authoring, governed agent access, and a complete execution trail. Up to 30×faster execution Compared to standard Drools 10 distributions in validated benchmarks. 20%Faster processing Compared to standard Drools 10 distributions in validated benchmarks. 300%ROI over three years Compared to alternative modernization paths. Direct founder conversation ## Talk directly to the people building Aletyx. Bring us the operation you need to build or modernize, the systems it touches, and where AI must fit. Work directly with Aletyx’s founders to map the right combination of decisions, workflows, agents, and governance. [Talk to a founder](https://aletyx.ai/contact/) [Start a guided pilot](https://aletyx.ai/free-trial/) --- # AI brings the intelligence. We make it accountable. Source: https://aletyx.ai/about-us/ Accountable automation for the age of AI For almost two decades, our team built the engines behind critical decisions and workflows at Red Hat, IBM, and in open source. We created Aletyx to make automation accountable in the age of AI. ## AI is automating the whole business. Accountability is what gives it the autonomy to run mission-critical work too. Accountability is what lets AI take on the decisions you have to stand behind: eligibility, a claim, a line of credit, a patient's treatment. We make those outcomes deterministic, explainable, auditable, and governed. It's what we've always built: the most widely adopted open-source foundation for accountable automation, Drools, jBPM, KIE Server, and Kogito, running inside much of the Fortune 500. AI brings the intelligence; we bring the trust. You don't start over. If you already run those engines, you move forward, and that stack now powers what comes next: the Accountable Agent, agentic where it can be, accountable where it must be. ### Deterministic, every time Same inputs, same outcome. No drift, no probabilistic guesswork behind a real decision. ### Explainable and on the record Every input, decision, and outcome captured automatically, in a form auditors can read and reviewers can follow. ### Governed before go-live Nothing ships until it's versioned and reviewed against the policy or regulation it enforces. ## Meet the team ![Alex Porcelli](https://aletyx.ai/_astro/alex.DSgiN440_Z8VELC.webp) ### Alex Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. ![Tim Wuthenow](https://aletyx.ai/_astro/tim.Bqy1ExdV_VKEm6.webp) ### Tim Co-founder & CCO More than 15 years putting rules, process, and AI to work where enterprise decisions matter. Focused on automation organizations can defend, not just deploy. ![Eduardo Cerqueira](https://aletyx.ai/_astro/eduardo.DeeWzaqE_2bTp7L.webp) ### Eduardo Co-founder & COO More than 20 years running cloud, DevOps, and CI/CD at production scale. Focused on reliable enterprise distributions and operations. ![Lara Lima](https://aletyx.ai/_astro/lara.B-MqE7vb_Z2ozeNa.webp) ### Lara Lima Software Engineer ![Mayna Camily](https://aletyx.ai/_astro/mayna.Di-YKdtv_1WVvB5.webp) ### Mayna Camily Software Engineer ![Maurício Rodrigues](https://aletyx.ai/_astro/mauricio.DIgOj1QR_KVz8h.webp) ### Maurício Rodrigues Software Engineer ![Wagner Farias](https://aletyx.ai/_astro/wagner.Br84CUD3_Z1yPG2q.webp) ### Wagner Farias Software Engineer ![Vitor Hugo Maia](https://aletyx.ai/_astro/vitor-hugo.ChUIQ2lN_14Ri1X.webp) ### Vitor Hugo Maia Software Engineer ![Ken Otto](https://aletyx.ai/_astro/ken.Dc-j6ZQ-_19TdE7.webp) ### Ken Otto Mortgage Industry Executive ![Juliana Conti](https://aletyx.ai/_astro/juliana.CLD6luQz_GAFxO.webp) ### Juliana Conti Marketing & Content ![Julio Faerman](https://aletyx.ai/_astro/julio-faerman.CKbnPuGs_Z1BBFAq.webp) ### Julio Faerman Marketing & Content ## What we stand for ### Accountability over hype Anyone can demo intelligence. We ship automation you can defend, to a regulator, an auditor, a board, not just in a sales meeting. ### Continuity over disruption The boldest thing in enterprise software is letting people keep what works. We move you forward without making you start over. ### Your success over the sale We don't tax your success. Pricing is flat and predictable, so as you scale, the upside stays yours, not metered back to us. ## Ready to make your AI accountable? Bring us the decision or workflow you can't afford to get wrong. Talk to the people building accountable AI, or see how we compare. Talk to Alex, our CEO [See how we compare](https://aletyx.ai/aletyx-vs-bamoe-vs-apache-kie/) --- # Model decisions. Skip the busywork. Source: https://aletyx.ai/ai-assistant/ Specialized AI for decision modeling Generate a complete model from a policy, spreadsheet, or prompt. Update an existing model with exact, reviewable edits. Ask AI Assistant to propose and run the tests. Try AI Assistant free for 14 days **$95** per user / month Credit card required. Cancel anytime. You won’t be charged during your trial. ![Aletyx AI Assistant proposing a threshold change with the exact previous and new values visible for approval](https://aletyx.ai/_astro/aletyx-card-02-ai-drafts-you-approve._HNT1HLE_2jjWDp.webp) Exact model diff **See every proposed change before it updates an existing model.** Standards-based **Portable decision models** Specialized for decision models Reviewable model-wide edits AI-assisted automated tests Purpose-built for decision work ## AI understands the whole model. Model-wide edits ## One request. All related edits. AI Assistant understands how decisions and expressions connect. It drafts the related changes together and shows an exact diff for review. ![AI Assistant showing coordinated model changes across a decision graph, change review, and decision table](https://aletyx.ai/_astro/aletyx-hero-final.CSwCsYLn_Z1rokWL.webp) Start from real source material ## Create or update a model. AI Assistant reads the policy or spreadsheet, then builds a complete new model or maps a revised policy to exact proposed edits. Create ### Build a complete model from a spreadsheet. AI Assistant interprets the table and generates the model as one coherent starting point. No manual transcription. ![Executable loan eligibility decision table generated from the supplied spreadsheet](https://aletyx.ai/_astro/spreadsheet-result.DkZpeEbG_1Ha5PL.webp)New decision model ![Loan eligibility spreadsheet supplied to AI Assistant](https://aletyx.ai/_astro/spreadsheet-source-focus.DpMbunim_1Tr1qS.webp)Spreadsheet Update ### Turn a revised policy into exact model edits. AI Assistant maps the policy to proposed changes in the existing model. Review each change before it touches the logic you already use. ![Existing discount decision model showing the exact revised values and pending change list](https://aletyx.ai/_astro/policy-revision-diff.COSyPqgn_U28NI.webp)Exact model diff ![Change summary from the revised discount policy supplied to AI Assistant](https://aletyx.ai/_astro/policy-revision.BgOve9f__1uRy0A.webp)Revised policy AI-assisted validation ## Generate tests. Catch mismatches. Ask AI Assistant to propose test cases and edge conditions. Pin exact outcomes, or use simple expressions to validate ranges and conditions. Run every case automatically against the model and spot differences immediately. ![Decision test table showing matching and differing expected outcomes](https://aletyx.ai/_astro/regression-tests-table.Cz-VGjYF_28gUlX.webp) Executable by design ## AI helps build the model. The model makes the decision. AI Assistant accelerates authoring and validation. The result remains an executable, inspectable decision model you can download as DMN and run on any compatible runtime. - Executable decision logic - Downloadable DMN - Compatible with DMN runtimes Use AI where you model ## Use AI in your browser. Nothing to install. Aletyx Playground is free to use. Activate AI Assistant to build or update a model in the browser, then download it and run it wherever you choose. Available now ### Aletyx Playground A free decision-modeling workspace. Add AI Assistant without installing anything. Available now ### Aletyx Decision Control Existing Decision Control users can add specialized decision-modeling AI directly in the product. Portable ### Your runtime, your choice Download standards-based DMN models and run them on any compatible runtime. Coming soon ### IDE extensions Bring AI-assisted decision modeling into your development environment. ![Aletyx Playground with a loan pre-qualification decision model and the integrated AI Assistant open](https://aletyx.ai/_astro/playground-real.D3oeTgWv_2hD1ud.webp) Specialized AI. Simple plan. ## Decision-modeling AI. $95/month. Use AI Assistant in Aletyx Playground or inside Decision Control. Your models remain downloadable and portable. AI Assistant ### Build, update, and test decision models faster. Generate complete models, make reviewable edits to models you already use, and automate use-case validation. **$95** per user / month Try AI Assistant free for 14 days Cancel anytime. You won’t be charged during your trial. #### What’s included: - Specialized decision-modeling AI built with frontier models - Works with existing decision models - Create and edit decisions from a policy, spreadsheet, or prompt - Review and approve edits to existing models - AI-assisted use-case validation with automated tests - Use AI Assistant in Aletyx Playground - Portable DMN models that run on compatible runtimes Credit card required. Usage limits apply. Prices shown don’t include applicable tax. Prices and plans are subject to change at Aletyx’s discretion. Frequently asked questions ## What to know before you try AI Assistant. 01 Do I need Aletyx Decision Control to use AI Assistant? No. You can use AI Assistant directly in Aletyx Playground, the free hosted modeling workspace. AI Assistant itself requires a subscription. Existing Decision Control users can also activate it inside Decision Control. 02 Is Aletyx Playground free? Yes. Aletyx hosts the Playground at no additional charge. AI Assistant requires an active subscription and is subject to usage limits, but there is no separate Playground or hosting fee. 03 Can I run the resulting models outside Aletyx? Yes. AI Assistant works with the DMN standard. You can download your models and run them in any compatible DMN runtime. 04 What can I use to create a decision? You can begin with a policy, spreadsheet, prompt, or existing decision model. 05 How does review differ for new and existing models? For a new decision, AI Assistant generates the complete model as one coherent starting point. There is no per-element approval loop. When changing an existing model, it presents exact diffs so you can accept or revert each edit before applying it. 06 How does AI-assisted validation work? AI Assistant helps you define the use cases and expected behavior that matter. Automated tests execute those scenarios against the model and show where actual results differ from expectations. 07 How does additional usage work? AI Assistant combines Aletyx decision-modeling models with frontier AI models. Your subscription includes usage. If you need more, you can purchase additional usage at rates aligned with the frontier models used. Current rates are shown before purchase. 08 What happens after the free trial? A credit card is required to begin the 14-day trial, but you will not be charged during it. Cancel anytime before the trial ends. Otherwise, the subscription continues at $95 per user per month, plus applicable tax. 09 Will AI Assistant be available in an IDE? IDE extensions are coming soon. Today, AI Assistant is available through Aletyx Playground and Aletyx Decision Control. Put AI to work ## Bring a model, policy, or spreadsheet. AI Assistant can build the model, draft the update, and generate the tests. Start in Aletyx Playground with nothing to install. Try AI Assistant free for 14 days $95 per user/month after the trial. Cancel anytime. --- # The complete enterprise platform for decision & workflow automation Source: https://aletyx.ai/aletyx-vs-bamoe-vs-apache-kie/ Aletyx vs. IBM BAMOE vs. Apache KIE Aletyx vs. IBM BAMOE vs. Apache KIE Aletyx delivers the only AI-native, enterprise-grade platform for both Decision Management and Intelligent Process Automation—with zero-rewrite migration paths that IBM and community alternatives can’t match. [Start Guided Pilot](https://aletyx.ai/free-trial/) [Read the Architecture Guide](https://aletyx.ai/contact/) ## The Aletyx platform Product Components What it Replaces Aletyx Decision Intelligence Aletyx Enterprise Build of Drools, Decision Control, Decision Tower Red Hat Decision Manager, IBM BAMOE (Decision), Apache KIE Drools Aletyx Intelligent Process Automation Aletyx Enterprise Build of Kogito, Aletyx Enterprise Build of KIE Server Red Hat PAM, IBM BAMOE (Process), jBPM 7, Apache KIE Kogito Product ### Aletyx Decision Intelligence Components Aletyx Enterprise Build of Drools, Decision Control, Decision Tower What it Replaces Red Hat Decision Manager, IBM BAMOE (Decision), Apache KIE Drools Product ### Aletyx Intelligent Process Automation Components Aletyx Enterprise Build of Kogito, Aletyx Enterprise Build of KIE Server What it Replaces Red Hat PAM, IBM BAMOE (Process), jBPM 7, Apache KIE Kogito ### Why Aletyx on top of community? Aletyx builds on the Apache KIE community stack. The value we add falls into two areas: Software Lifecycle and Product Capabilities. ## Software lifecycle & support Community releases follow an open-source model. Fixes arrive when contributors have time. Releases ship when builds pass, but the project does not run a systematic hardening process. Vulnerabilities do get addressed, but timelines vary. ### Defined release cycles On a predictable schedule. ### SLAs for issue resolution That run on your timeline. ### Professional support Rather than volunteer availability. ### Systematic security hardening Before each release. ## Product capabilities Beyond lifecycle, Aletyx extends the community stack with capabilities that don't exist in Apache KIE or IBM BAMOE—true horizontal scalability, AI-native features, enterprise governance, and zero-rewrite migration paths. Capability Aletyx IBM BAMOE Apache KIE Business User Authoring ✅ ⚠️ Limited ⚠️ Limited AI Assistant Editor ✅ ❌ ❌ Zero-Rewrite jBPM v7 Migration ✅ ❌ N/A True horizontal scalability ✅ ❌ ❌ Business Governance ✅ ❌ ❌ Native GenAI/MCP ✅ ⚠️ API wrapper ❌ 24x7 Support ✅ ✅ ❌ Fixed Pricing ✅ ❌ Free; self-supported Capability ### Business User Authoring Aletyx✅ IBM BAMOE⚠️ Limited Apache KIE⚠️ Limited Capability ### AI Assistant Editor Aletyx✅ IBM BAMOE❌ Apache KIE❌ Capability ### Zero-Rewrite jBPM v7 Migration Aletyx✅ IBM BAMOE❌ Apache KIE N/A Capability ### True horizontal scalability Aletyx✅ IBM BAMOE❌ Apache KIE❌ Capability ### Business Governance Aletyx✅ IBM BAMOE❌ Apache KIE❌ Capability ### Native GenAI/MCP Aletyx✅ IBM BAMOE⚠️ API wrapper Apache KIE❌ Capability ### 24x7 Support Aletyx✅ IBM BAMOE✅ Apache KIE❌ Capability ### Fixed Pricing Aletyx✅ IBM BAMOE❌ Apache KIE Free; self-supported AI-Native Platform ## AI assistant authoring tool Natural-language to Decision/Process authoring Aletyx is shipping AI Assistant editors for both Decision and Workflow products. Convert business requirements expressed in natural language directly to DMN models and BPMN processes with real-time validation. Neither IBM nor Apache KIE offer AI-assisted authoring. Capability Aletyx IBM BAMOE Apache KIE AI assistant authoring tool ✅ ❌ ❌ Capability ### AI assistant authoring tool Aletyx✅ IBM BAMOE❌ Apache KIE❌ AI-Native Platform ## Process triggering from AI agents via MCP Native AI agent orchestration—not bolted on Aletyx implements native Model Context Protocol (MCP) integration, allowing AI agents to trigger, query, and interact with business processes. Your existing workflows become tools that AI agents can invoke with full governance and audit traceability. IBM has added some MCP capabilities, but it’s bolted on—brittle and limited. Aletyx MCP is native to the platform architecture. Capability Aletyx IBM BAMOE Apache KIE Process triggering from AI agents via MCP ✅ ⚠️ Bolt-on ❌ Capability ### Process triggering from AI agents via MCP Aletyx✅ IBM BAMOE⚠️ Bolt-on Apache KIE❌ AI-Native Platform ## AI agent node for ad hoc tasks Embed autonomous AI decision-making within processes Add AI Agent nodes directly in your BPMN processes for tasks requiring autonomous decision-making. The agent operates within governed guardrails, enabling flexible automation while maintaining compliance and auditability. Capability Aletyx IBM BAMOE Apache KIE AI agent node for ad hoc tasks ✅ ❌ ❌ Capability ### AI agent node for ad hoc tasks Aletyx✅ IBM BAMOE❌ Apache KIE❌ AI-Native Platform ## Direct LLM invocation node Native LLM integration in workflow orchestration Invoke large language models directly from workflow nodes—for summarization, classification, extraction, or generation tasks. No custom code required; configure LLM calls as part of your process definition. Capability Aletyx IBM BAMOE Apache KIE Direct LLM invocation node ✅ ✅ ❌ Capability ### Direct LLM invocation node Aletyx✅ IBM BAMOE✅ Apache KIE❌ AI-Native Platform ## LLM-assisted decision explainability AI-powered decision explanation with validation Generate natural language explanations of decision logic while maintaining full auditability. Essential for regulated industries requiring transparency in automated decisions. Capability Aletyx IBM BAMOE Apache KIE LLM-assisted decision explainability ✅ ❌ ❌ Capability ### LLM-assisted decision explainability Aletyx✅ IBM BAMOE❌ Apache KIE❌ AI-Native Platform ## Governed composite AI Symbolic + GenAI with full auditability Combine the precision of rule-based decisions with the flexibility of generative AI—all within a governed framework. Rules engines and process orchestration serve as master controllers, ensuring AI outputs align with verified guidelines. Capability Aletyx IBM BAMOE Apache KIE Governed composite AI ✅ ❌ ❌ Capability ### Governed composite AI Aletyx✅ IBM BAMOE❌ Apache KIE❌ Workflow & Process Automation ## True horizontal scalability Multi-node design without leader election Aletyx Enterprise Build of Kogito is the first distribution to offer true horizontal scalability by eliminating leader election bottlenecks. IBM BAMOE and Apache KIE distributions rely on leader election, creating a single point of failure that limits throughput under load. Capability Aletyx IBM BAMOE Apache KIE True horizontal scalability ✅ ❌ ❌ Capability ### True horizontal scalability Aletyx✅ IBM BAMOE❌ Apache KIE❌ Workflow & Process Automation ## Scalable job service Enterprise-grade timer and async job handling Timer events and async jobs are the first components to fail under leader election constraints. Aletyx distributes job execution across all available nodes with no coordinator dependency, so your high-volume process automation scales linearly without a single point of failure. Capability Aletyx IBM BAMOE Apache KIE Scalable job service ✅ ❌ ❌ Capability ### Scalable job service Aletyx✅ IBM BAMOE❌ Apache KIE❌ Workflow & Process Automation ## Drop-in KIE Server replacement Modernize jBPM 7 without rewrites Aletyx Enterprise Build of KIE Server provides a drop-in modern replacement for jBPM v7 and KIE Server. Your existing process definitions, APIs, and integrations continue working. IBM BAMOE and Apache KIE force a complete rewrite to Kogito architecture. Capability Aletyx IBM BAMOE Apache KIE Drop-in KIE Server replacement ✅ ❌ ❌ Capability ### Drop-in KIE Server replacement Aletyx✅ IBM BAMOE❌ Apache KIE❌ Workflow & Process Automation ## Safe migration path from jBPM 7 Kogito is great for greenfield—not for production migrations Kogito is an excellent choice for new projects built from scratch. But upgrading existing jBPM 7 production workloads to Kogito is a different story entirely. Different engine. Different capabilities. Different architecture. RISK. The forced rewrite isn’t just expensive—it’s dangerous. Process state management, persistence patterns, and runtime behaviors all changed fundamentally. Edge cases and behaviors that took years to stabilize in your jBPM 7 workloads must be re-discovered and re-fixed. IBM BAMOE and Apache KIE both force this path. Aletyx provides evolution, not revolution. Our Enterprise Build of KIE Server is a drop-in replacement that preserves your production stability. Capability Aletyx IBM BAMOE Apache KIE Safe migration path from jBPM 7 ✅ ❌ ❌ Capability ### Safe migration path from jBPM 7 Aletyx✅ IBM BAMOE❌ Apache KIE❌ Decision Management ## Business Central / Decision Control Visual authoring for business users and analysts IBM turned a decision management system into a developer toolkit. BAMOE v9+ removed Business Central entirely—no authoring UI, no governance dashboards, API-only focus with no business audience. Aletyx Decision Control provides modern authoring and execution for both business and technical users. Capability Aletyx IBM BAMOE Apache KIE Business Central / Decision Control ✅ ❌ ⚠️ Limited Capability ### Business Central / Decision Control Aletyx✅ IBM BAMOE❌ Apache KIE⚠️ Limited Decision Management ## Zero-rewrite Drools migration Modernize Drools 7 without rewrites Aletyx Enterprise Build of Drools restores backward compatibility with legacy Drools, RHDM, and BRMS projects, including features IBM removed in v9 and capabilities that community Drools 10 changed. Your DRL, DMN, and BPMN assets carry forward — runtime upgrade, not a rewrite project. Organizations evaluating OSS Drools 10 or IBM BAMOE face 12-24 months of rewrite work. Capability Aletyx IBM BAMOE Apache KIE Zero-rewrite Drools migration ✅ ❌ ❌ Capability ### Zero-rewrite Drools migration Aletyx✅ IBM BAMOE❌ Apache KIE❌ Decision Management ## Rules orchestration support Preserve your existing ruleflow patterns BPMN-based rules orchestration has long been a best practice for complex rule sets. Drools 10 and IBM BAMOE fundamentally changed this capability. Aletyx preserves it. Capability Aletyx IBM BAMOE Apache KIE Rules orchestration support ✅ ❌ ❌ Capability ### Rules orchestration support Aletyx✅ IBM BAMOE❌ Apache KIE❌ Decision Management ## Excel decision table compatibility Your xls decision tables work without refactoring Drools 7 loads Excel decision tables with specific expectations around headers, type coercion, null handling, and cell expression semantics. These behaviors changed in Drools 10. Aletyx preserves the original semantics. Capability Aletyx IBM BAMOE Apache KIE Excel decision table compatibility ✅ ⚠️ ⚠️ Capability ### Excel decision table compatibility Aletyx✅ IBM BAMOE⚠️ Apache KIE⚠️ Decision Management ## Full DMN 1.5+ support Latest Decision Model and Notation standards All three platforms support DMN, but Aletyx is actively advancing to DMN 1.6 with enhanced tooling. Aletyx provides the most complete DMN implementation with visual model comparison and AI-assisted explainability. Capability Aletyx IBM BAMOE Apache KIE Full DMN 1.5+ support ✅ ✅ ✅ Capability ### Full DMN 1.5+ support Aletyx✅ IBM BAMOE✅ Apache KIE✅ Enterprise Governance & Security ## Maker/checker governance model Built-in approval workflows for regulated industries Financial services, healthcare, and insurance require maker/checker approval workflows before decisions and processes go to production. Aletyx Decision Tower provides native RBAC, multi-environment promotion (dev → test → prod), and Git integration for controlled rollouts. Capability Aletyx IBM BAMOE Apache KIE Maker/checker governance model ✅ ❌ ❌ Capability ### Maker/checker governance model Aletyx✅ IBM BAMOE❌ Apache KIE❌ Enterprise Governance & Security ## CVE management & security lifecycle Proactive security scanning with SLAs Aletyx provides dedicated security teams that scan for vulnerabilities, manage CVE responses, and deliver patches with enterprise SLAs. Apache KIE has no CVE ownership. Capability Aletyx IBM BAMOE Apache KIE CVE management & security lifecycle ✅ ✅ ❌ Capability ### CVE management & security lifecycle Aletyx✅ IBM BAMOE✅ Apache KIE❌ Enterprise Governance & Security ## Audit trails & compliance Built-in execution history for regulatory compliance Aletyx provides comprehensive audit trails and performance dashboards built into the platform for both decisions and processes. With IBM BAMOE and Apache KIE, you have to build your own audit infrastructure from scratch. Capability Aletyx IBM BAMOE Apache KIE Audit trails & compliance ✅ ⚠️ Build your own ⚠️ Build your own Capability ### Audit trails & compliance Aletyx✅ IBM BAMOE⚠️ Build your own Apache KIE⚠️ Build your own Support & Operations ## 24x7 enterprise support SLA-backed support from the original Drools/jBPM architects Aletyx support comes directly from the original Drools/jBPM architects with 17+ years of experience and Apache KIE PPMC membership. We know the engines inside and out because our founders built them. Capability Aletyx IBM BAMOE Apache KIE 24x7 enterprise support ✅ ✅ ❌ Capability ### 24x7 enterprise support Aletyx✅ IBM BAMOE✅ Apache KIE❌ Pricing & Total Cost of Ownership ## Fixed annual pricing Predictable costs without processor-based licensing complexity Aletyx offers transparent, fixed annual tiers: Decision Intelligence: $25K-$100K/year & Intelligent Process Automation: $50K-$200K/year IBM uses complex processor-based licensing that can reach six-figure annual costs for modest deployments. Apache KIE is “free” but carries substantial hidden operational and risk costs. Capability Aletyx IBM BAMOE Apache KIE Fixed annual pricing ✅ ❌ “Free” Capability ### Fixed annual pricing Aletyx✅ IBM BAMOE❌ Apache KIE “Free” Pricing & Total Cost of Ownership ## No forced rewrites Modernize without 12-24 months of rewrite cost IBM BAMOE and Apache KIE migrations require 12-24 months of rewrite effort for both Drools and jBPM workloads—with no new business value delivered. Aletyx provides a migration path, not a rewrite project. The Kogito rewrite is especially dangerous because its different architecture jeopardizes core business stability. Capability Aletyx IBM BAMOE Apache KIE No forced rewrites ✅ ❌ ❌ Capability ### No forced rewrites Aletyx✅ IBM BAMOE❌ Apache KIE❌ Frequently Asked Questions ## Answers to your CFO's questions [View plans](https://aletyx.ai/pricing/) 01 Can I just upgrade to open-source Drools 10 or Kogito? Technically yes—but you'll inherit every breaking change from the Kogito rewrite, lose production-proven features such as the Business Central authoring environment, and have no commercial SLA. Aletyx Enterprise gives you the Drools-10 engine with backward-compatible APIs, certified migration tooling, and enterprise support—so you modernise without gambling production stability. 02 Will IBM BAMOE preserve my Drools 7 or jBPM 7 workloads? BAMOE 9.x is based on the Kogito rewrite, which drops traditional KIE Server, Business Central, and the jBPM 7 process engine. Migrating to BAMOE means refactoring rule assets, re-integrating tooling, and accepting IBM's release cadence on a narrower feature set. Aletyx supports a direct upgrade path from Drools 7 / jBPM 7 that preserves existing KIE assets and APIs—no rewrite required. 03 Why is the Kogito rewrite dangerous for existing workloads? Kogito was designed as a cloud-native, greenfield architecture. It replaced the KIE Server runtime, removed Business Central, and broke backward compatibility with Drools 7 / jBPM 7 APIs. For teams running production rule services or process applications, "upgrading" to Kogito-based platforms (including BAMOE 9.x and raw Apache KIE) means rewriting integration code, revalidating every rule, and retraining authors—an unplanned, high-risk project. 04 Is Apache KIE really "free"? The license cost is zero; the operational cost is not. You take on security patching, version qualification, performance tuning, and 24/7 incident response with no guaranteed SLA. For regulated or revenue-critical workloads, the total cost of self-support routinely exceeds the price of a commercial subscription—and the risk exposure is uncapped. 05 What AI capabilities does Aletyx offer? Aletyx embeds AI across the decision lifecycle: - Natural-language rule authoring – describe intent and generate executable DRL. - Intelligent rule analysis – detect conflicts, redundancies, and coverage gaps automatically. - Decision simulation – run what-if scenarios against production data before deployment. - Continuous optimization – closed-loop feedback refines rules based on real outcomes. These capabilities are built into the platform; they are not bolt-on add-ons. 06 Why do I need enterprise support if the software is open source? Yes. Aletyx is built for continuity across prior-generation production workloads so you can modernize without refactoring business logic. Your last chance ## Predictable Performance.Predictable Costs. Stop budgeting for "unexpected overages." Lock in your modernization cost today. [Get a Custom Quote](https://aletyx.ai/contact/) Response within 24 hours. No obligation. --- # Alex Porcelli Source: https://aletyx.ai/authors/alex-porcelli/ ![Alex Porcelli](https://aletyx.ai/_astro/alex.DSgiN440_Z8VELC.webp) Aletyx author Co-founder & CEO Alex Porcelli is co-founder and CEO of Aletyx. He has spent nearly two decades building Drools, jBPM, and Kogito, including product leadership at Red Hat and IBM. An Apache KIE PPMC member and longtime open-source contributor, Alex is now focused on accountable automation for the age of AI. [LinkedIn](https://www.linkedin.com/in/alexporcelli/) Writing ## Articles by Alex ### [Decision Tables: What They Look Like for Business Users](https://aletyx.ai/blog/decision-tables-for-business-users/) Decision tables make business policies visible, testable, and changeable without code. See what they look like when business people use them, and how AI accelerates authoring. Topics: Decision Intelligence, DMN. Reading time: 6 min ### [The Gap Between Policy and the Model](https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/) Decision analysts understand policy changes first, but often can't ship them to production. Learn how Aletyx Decision Control and the Aletyx AI Assistant close the gap between business intent and working decision models. Topics: AI Assistant, Artificial Intelligence. Reading time: 6 min ### [Aletyx Officially Listed as Vendor of Apache KIE](https://aletyx.ai/news/aletyx-official-apache-kie-vendor/) Aletyx is thrilled to announce our official listing as a vendor on the Apache KIE commercial support page, underscoring our commitment to the open source ecosystem and enterprise community. Topics: Apache KIE, Drools. Reading time: 3 min ### [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ### [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ### [Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025](https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/) At Arc of AI 2025, Aletyx co-founder Alex Porcelli shared groundbreaking insights on combining Large Language Models with Rule Engines to create more controlled and reliable AI systems. Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ### [Essential Concepts for Navigating Enterprise AI Trends](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/) Cut through the noise and buzzwords and understand the foundational concepts associated with AI, their applications, and the trade-offs enterprises must consider. Topics: Artificial Intelligence, Model Context Protocol. Reading time: 8 min ### [Overcoming Challenges: Enterprise Path to Intelligent Solutions](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/) Why are intelligent systems often associated with lack of compliance? Unpack the trade-offs derived from the characteristics of the types. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 4 min ### [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/) While LLMs capture headlines, enterprise AI success requires a broader architectural approach. Discover how to build intelligent systems that combine multiple AI paradigms for real-world business applications. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 5 min ### [The Missing Manual for Kogito: How to Use Java APIs Instead of Auto-Generated REST Endpoints](https://aletyx.ai/blog/how-to-use-java-apis-with-kogito-process/) Learn how to trigger Kogito BPMN processes using the Java API—without relying on auto-generated REST endpoints. Topics: Enterprise Enablement, Apache KIE. Reading time: 3 min --- # Julio Faerman Source: https://aletyx.ai/authors/julio-faerman/ ![Julio Faerman](https://aletyx.ai/_astro/julio-faerman.CKbnPuGs_Z1BBFAq.webp) Aletyx author Marketing & Content Julio Faerman works in Marketing & Content at Aletyx. He translates technical and regulatory subjects into practical resources for enterprise teams, including Aletyx's coverage of mortgage AI governance. Writing ## Articles by Julio ### [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min --- # Ken Otto Source: https://aletyx.ai/authors/ken-otto/ ![Ken Otto](https://aletyx.ai/_astro/ken.Dc-j6ZQ-_19TdE7.webp) Aletyx author Mortgage Industry Executive Ken Otto is Mortgage Industry Executive at Aletyx. He connects mortgage-industry requirements with Aletyx's work on accountable automation and AI governance, helping ensure its mortgage resources reflect the needs of lenders and their partners. Writing ## Articles by Ken ### [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min --- # Tim Wuthenow Source: https://aletyx.ai/authors/tim-wuthenow/ ![Tim Wuthenow](https://aletyx.ai/_astro/tim.Bqy1ExdV_VKEm6.webp) Aletyx author Co-founder & CCO Tim Wuthenow is co-founder and CCO of Aletyx. For more than 15 years, he has worked with business rules, process automation, and AI in enterprise environments, including at IBM and Red Hat. At Aletyx, he focuses on helping organizations put accountable automation to work where their decisions matter. [LinkedIn](https://www.linkedin.com/in/timwuthenow/) Writing ## Articles by Tim ### [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ### [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ### [Enabling Teams with Apache KIE 10: Aletyx's Workshop on Kogito-based Workflows](https://aletyx.ai/case-studies/aletyx-workshop-kogito/) Aletyx recently delivered an Apache KIE 10 Workshop to a science and technology customer, providing hands-on training in Kogito workflows, decision modeling, and production-ready practices. Topics: Enterprise Enablement, Apache KIE. Reading time: 2 min --- # Meeting the 2026 GSE Governance Rules with Accountable AI Source: https://aletyx.ai/blog/2026-mortgage-gse-compliance/ [Governance & Compliance](https://aletyx.ai/topics/governance-and-compliance/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) August 5, 2026 11 min ![A hand placing an orange model house among black model houses](https://aletyx.ai/_astro/houses-hero.CRAdApM2_Z2ebdzO.webp) By [Julio Faerman](https://aletyx.ai/authors/julio-faerman/) and [Ken Otto](https://aletyx.ai/authors/ken-otto/) Published August 5, 2026 ## Meeting the 2026 GSE Governance Rules with Decision Management > **Key takeaways** > > - Freddie Mac’s AI/ML governance requirements have been **in force since March 3, 2026**; Fannie Mae’s take effect **August 6, 2026**. Business partners of either GSE that use AI anywhere in that pipeline should adapt. Also, it is an example of how policies are adapting to AI applications and how responsibilities are divided. > - The rules cover *all* AI you use, including AI embedded in vendor tools. The model can be outsourced, but the accountability cannot. > - The hardest obligation is **disclosure**: when requested, one must show what AI is used, how, and with what safeguards. > - Done right, every decision carries five artifacts: policy version, inputs, decision path, approval, tests. With those, disclosure becomes a query instead of a fire drill. AI governance in mortgage lending stopped being a best practice this year. It became a *contractual condition* of doing business with the government-sponsored enterprises (GSEs): Fannie Mae and Freddie Mac. Two dates made it official: - **March 3, 2026** — Freddie Mac’s [Guide Section 1302.8](https://guide.freddiemac.com/app/guide/section/1302.8), *Use of artificial intelligence and machine learning*, took effect. Its requirements are already in force. - **August 6, 2026** — Fannie Mae’s [Lender Letter LL-2026-04](https://singlefamily.fanniemae.com/news-events/lender-letter-ll-2026-04-governance-framework-use-artificial-intelligence-and-machine-learning), *Governance framework on use of artificial intelligence and machine learning*, becomes effective. Both frameworks cover any AI or machine learning a seller uses in connection with originating loans sold to, or servicing loans on behalf of, the GSEs. The scope is not limited to models the lender developed in-house: AI embedded in the third-party tools and vendor platforms a lender relies on counts just the same, and *the lender remains the accountable party* for it. If you sell to or service for either GSE and you use AI anywhere in that pipeline, these rules apply to you now. And beyond the GSEs, this is an example of how policies are evolving to adjust to AI applications across the software supply chain. ## What the GSEs actually require In short: both GSEs require senior-approved AI policies, continuous risk management, governance of vendor AI, and on-demand disclosure of how AI is used. Read together, the two frameworks converge on four obligations: **1\. Clear, owned, senior-approved policies.** Freddie Mac requires AI/ML policies and procedures approved by senior management, at a minimum the CIO, CTO, CISO, or CRO (or equivalents). Those policies must be communicated to every employee whose job touches AI, with a named owner who implements, maintains, and reviews them at least annually. Fannie Mae’s letter mirrors this: transparent policies covering the development, implementation, use, and maintenance of any AI/ML system, incorporating the characteristics of trustworthy and ethical AI, reviewed annually by an accountable owner. **2\. Continuous risk management.** Both GSEs expect you to map, measure, and manage AI risk — the language of the [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) — on an ongoing basis, calibrated to your risk tolerance. Freddie Mac is explicit about the operational details: assess AI/ML for threats like data poisoning and adversarial inputs; regularly monitor systems for performance, security breaches, and bias; conduct internal and external audits against standards such as NIST 800-53 and ISO 27001; and apply segregation of duties so accountability structures are clear and documented across the organization. **3\. Oversight of third-party AI.** Fannie Mae requires seller/servicers to “[manage risks and appropriate governance of subcontractor and vendor use of AI/ML that is no less protective of these requirements](https://singlefamily.fanniemae.com/news-events/lender-letter-ll-2026-04-governance-framework-use-artificial-intelligence-and-machine-learning).” Freddie Mac adds an indemnification clause: the seller/servicer holds Freddie Mac harmless for liabilities arising from its use of AI/ML, foreseeable or not. **4\. Show your work — on demand.** Both frameworks contain nearly identical language: whenever Fannie Mae or Freddie Mac asks, the seller/servicer must *promptly disclose* the types of AI/ML used, the purpose and manner of use, the safeguards in place to mitigate risk, and any other information the GSE may require. That fourth obligation is the one that changes daily operations. Policies can be written. Risk frameworks can be documented. But *prompt disclosure* is an operational test: when the request comes, what can you actually produce? ## The gap between having a policy and proving a decision Most lenders’ honest answer today is: a policy PDF, a vendor contract, and a scramble. That’s because the AI actually transforming mortgage work today — tasks like document extraction, income analysis, chat-based borrower assistance, and automated condition clearing — is largely probabilistic. Generative AI is extraordinary at handling ambiguity: reading a messy paystub, summarizing a hardship letter, extracting figures from a bank statement. But probabilistic systems are, by construction, hard to govern at the level the GSEs now demand. The same input can produce different outputs. The reasoning is not inspectable rule by rule. Even simple questions, such as “Why was this borrower declined?”, sometimes have no recoverable answer. The way out is not to avoid AI. It is to separate interpretation from decisioning. Let the AI software read the document. Let it extract, summarize, and structure. Then hand the structured facts to an explicit, versioned decision model covering eligibility rules, income calculation logic, pricing adjustments, and loss-mitigation waterfalls. That model produces the outcome deterministically. Identical inputs always produce identical outputs. Every rule that fired is recorded. The decision logic is an asset the business owns, reviews, and approves, not a behavior buried in model weights. This is decision management, and it is precisely the discipline the 2026 frameworks reward. ## The evidence trail: five things every decision should carry When a GSE reviewer, internal auditor, or regulator asks about an AI-assisted decision, an accountable architecture lets you produce five artifacts for *any individual decision*, on demand: 1. **Policy** — the exact version of the decision model that was in force when the decision was made. 2. **Inputs** — the precise data the decision saw, including what upstream AI extracted. 3. **Decision path** — every rule and branch evaluated, in order, with intermediate results. 4. **Approval** — who reviewed and approved that model version, and when. 5. **Tests** — the test scenarios that version passed before it reached production. If you can produce those five things for any loan file, “prompt disclosure” stops being a fire drill and becomes a query. ## A concrete scenario: one loan file, months later Here is what the difference looks like on a single file. A self-employed borrower applies in September 2026. An AI document service reads two years of tax returns and bank statements and extracts the raw figures — no human re-keying, minutes instead of hours. Those figures flow into the lender’s income-calculation decision model (version 3.2), which computes qualifying monthly income of $8,410, and then into the eligibility model (version 5.1), which approves the loan: the debt-to-income rule evaluates to 41%, under the program’s 45% threshold, and every other eligibility rule passes. Fourteen months later, the loan lands in a GSE quality-control sample, and the disclosure request arrives: *what role did AI play in this decision, and what safeguards governed it?* With an accountable architecture, the answer takes minutes. The lender produces the five artifacts: eligibility model v5.1 as the policy in force; the extracted figures the decision actually saw; the full decision path, rule by rule, including the 41% debt-to-income result; the credit-policy owner’s approval of v5.1, dated before the loan was decided; and the regression test suite that version passed before release. The AI’s role is fully disclosed, including the inputs it extracted, and the decision-maker of record is a versioned, tested, approved model. Without an accountable architecture, the answer would probably be much more precarious: a policy PDF, a vendor contract, and several weeks of reconstructing what the system probably did. ## How to build accountable AI with Aletyx [Aletyx](https://aletyx.ai/) is an enterprise platform for **Accountable AI**: automation where every outcome is explainable, auditable, and governed. For mortgage lenders facing the 2026 mandates, the pieces map directly onto the GSE requirements. ### Decisions as governed, versioned assets [Aletyx Decision Control](https://aletyx.ai/docs/decision-control/overview) manages business decisions the way you manage code — with version control, testing, and CI/CD — but designed for the people who actually own mortgage policy: - **Author decisions visually** in industry-standard DMN notation: eligibility matrices, income calculation logic, pricing grids, servicing waterfalls. Business analysts model the policy directly; developers integrate it. No black boxes, no logic scattered across spreadsheets and code. - **Governed progression through environments.** Models move Dev → Test → Production with automated governance checks and built-in approval workflows enforcing the four-eyes principle — no one approves their own change. That is Freddie Mac’s segregation-of-duties requirement, implemented in the deployment pipeline rather than in a binder. - **Audit everything.** Who changed what, when, and why — captured automatically for every model, every version, every environment. When the disclosure request arrives, the answer is already recorded. - **Test naturally.** Analysts and compliance teams validate decision behavior by asking questions in plain English — “What happens if income is $85,000 and credit score is 720?” — and reviewers can probe edge cases before approving a release. Continuous validation is exactly the “regular monitoring and review” posture both GSEs require. ![Aletyx Decision Control Rules Editor](https://aletyx.ai/_astro/rules-editor.DHRm-u2K_ZHQMBM.webp) ### Pairing AI with accountable decisions Aletyx’s [Decisions + GenAI](https://aletyx.ai/docs/decisions-genai) approach uses the Model Context Protocol (MCP) to connect AI assistants like Claude with Drools and DMN decision services and process orchestration. The division of labor is deliberate: - The **AI integration layer** lets the AI do what it’s best at: understanding documents, language, and context. - The **decision layer** executes the accountable logic, with full traceability of which rules fired and why. - The **process layer** orchestrates the end-to-end flow — origination steps, servicing workflows, human review escalations — so the whole pipeline, not just a single decision, is governed. The result is that AI accelerates your mortgage operation *without* becoming the decision-maker of record. The decision-maker of record is a versioned, tested, approved model your business owns and can defend. ## AI in mortgage: explainable, repeatable, auditable. The 2026 GSE frameworks are not an obstacle to AI adoption in mortgage. They are a specification for doing it sustainably. Lenders who treat governance as an evidence-producing architecture, rather than a documentation exercise, will move faster: they can adopt new AI capabilities confidently because the accountable decision layer beneath them doesn’t change. That is the “accountable” standard we build for: **Explainable. Repeatable. Auditable.** ## Frequently asked questions **When do the new GSE AI governance rules take effect?** Freddie Mac’s requirements ([Guide Section 1302.8](https://guide.freddiemac.com/app/guide/section/1302.8)) have been in force since March 3, 2026. Fannie Mae’s ([Lender Letter LL-2026-04](https://singlefamily.fanniemae.com/news-events/lender-letter-ll-2026-04-governance-framework-use-artificial-intelligence-and-machine-learning)) become effective August 6, 2026. **Do the rules apply if we only use AI through vendor tools?** Yes. Both frameworks cover AI embedded in third-party software — document processing services, pricing engines, servicing platforms — and the seller/servicer remains the accountable party. Fannie Mae requires vendor governance “no less protective” than your own, and Freddie Mac adds an indemnification obligation on top. **Do we have to stop using generative AI in origination or servicing?** No. Neither GSE prohibits any class of AI. What the rules demand is governance: knowing where AI is used, managing its risks, and being able to disclose and defend outcomes. The practical pattern is to let generative AI handle ambiguous inputs such as documents, language, and context, while a versioned decision model makes the accountable decision. **What does “prompt disclosure” actually require?** On request, you must promptly tell the GSE what types of AI/ML you use, the purpose and manner of use, and the safeguards in place to mitigate risk — plus any other information they require. The operational test is whether you can produce that evidence for a specific loan file, not just point to a policy document. **What is decision management, and why does it help here?** Decision management is the discipline of expressing business decisions — eligibility, income calculation, pricing, loss mitigation — as explicit, versioned, and testable models, rather than burying them in code, spreadsheets, or model weights. Because those models are predictable, identical inputs always produce identical outputs, and every rule that fired can be replayed — which is exactly the evidence the 2026 frameworks call for. --- *See how Aletyx Decision Control builds the evidence trail behind every decision: [docs.aletyx.ai](https://aletyx.ai/docs) — or try it yourself in the [Playground](https://playground.aletyx.ai/).* ## References 1. [Use of artificial intelligence and machine learning (Guide Section 1302.8)](https://guide.freddiemac.com/app/guide/section/1302.8) — Freddie Mac 2. [Governance framework on use of artificial intelligence and machine learning (Lender Letter LL-2026-04)](https://singlefamily.fanniemae.com/news-events/lender-letter-ll-2026-04-governance-framework-use-artificial-intelligence-and-machine-learning) — Fannie Mae 3. [AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) — National Institute of Standards and Technology ## About the authors [Julio Faerman](https://aletyx.ai/authors/julio-faerman/) Marketing & Content Creates practical Aletyx content about enterprise automation, AI governance, and the policies shaping accountable decisions. [More from Julio](https://aletyx.ai/authors/julio-faerman/) [Ken Otto](https://aletyx.ai/authors/ken-otto/) Mortgage Industry Executive Brings mortgage-industry perspective to Aletyx's work on accountable automation and AI governance. [More from Ken](https://aletyx.ai/authors/ken-otto/) --- # The Gap Between Policy and the Model Source: https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/ AI Assistant [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) March 16, 2026 6 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published March 16, 2026 When a regulation changes, the decision analyst is usually the first person who understands what needs to happen. But they are rarely the person who can actually change the system. **You know the policy. The model is the gap.** The new threshold. The updated eligibility rule. The exception that now needs to exist. For someone who works with these policies every day, the logic usually clicks pretty fast. Turning that understanding into a working DMN decision model is where things slow down. Decision models sit in a strange place between business and IT. In theory they belong to the business. They represent policies, rules, business intent. But in practice they still look technical. FEEL expressions, dependencies between nodes, decision tables, data types that behave differently than you expect. And in many organizations analysts cannot even touch the model. A policy change becomes a ticket. IT queues it, it waits for the next sprint, and something that should take an hour to update can easily take days or weeks before it shows up in the system. ## Closing that gap This is exactly the kind of problem that tools like **Aletyx Decision Control** were built to solve. Instead of routing every policy change through engineering, analysts and domain experts can build and evolve decision models themselves. They can explore the logic, run scenarios, and update models as policies change. That helps a lot. Still, decision models can grow into fairly complex systems. Tables depend on other tables. Inputs move through several nodes before producing an outcome. A small change in one place can quietly affect something somewhere else in the model. And when the logic gets complicated, people naturally want a second pair of eyes. A colleague. An architect. Sometimes the person who originally built the model. Not because the change is impossible. Just because complex logic benefits from another perspective. ## Where an AI assistant helps This is where an AI assistant starts to make sense. And it is worth saying this upfront. We are still early. If you remember the first versions of GitHub Copilot, that is roughly the stage we are in. Copilot did not write entire applications. It helped with pieces of code, suggested patterns, saved developers time looking things up. Useful right away, but clearly the beginning of something bigger. AI for enterprise decision modeling is entering that same phase. The **Aletyx AI Assistant** is already helpful today, especially when analysts are dealing with complex or unfamiliar models. ## What if you could just ask the model? One of the most useful things the assistant does is simply help you understand a model. You can open a model and ask things like: - What does this node do? - Where is this threshold used? - What feeds into this decision table? Instead of digging through the model manually, the assistant reads the structure of the decision model and explains it back in plain language. What used to take a lot of clicking around can turn into a short conversation. ## Describing changes in plain language You can also describe updates the way you would explain them to a colleague. For example: update the income threshold to sixty five thousand everywhere it appears. The assistant looks at the model, finds where that value is used, and proposes the updates. Nothing changes automatically. The model shows exactly where edits are suggested and the analyst decides what to accept or reject. The person who understands the policy stays in control of the logic. ## The second pair of eyes Decision models are very good at hiding edge cases. After making a change, you can ask the assistant to review the model and point out scenarios that might not be covered, unusual combinations of inputs, or boundaries that behave in surprising ways. It is basically that second pair of eyes. Just one that never gets tired of reading through decision logic. And before shipping the change, the assistant can also generate test scenarios. Boundary values, odd combinations of inputs, cases production data may never naturally hit. It does not replace proper testing, but it helps teams cover ground they rarely have time to explore manually. ## Starting without a blank page Sometimes the starting point is not a model at all. It might be a regulation document, a policy draft, or a rough description of how a decision should work. The assistant can generate an initial decision model structure from that input. It will not be perfect, but it gives analysts something to start from instead of staring at a blank canvas. ## The beginning of a new workflow We are still early in this space. But the tools are already good enough to start changing how analysts work. And if the evolution of tools like Copilot taught us anything, it is that the teams who start experimenting early often end up shaping what comes next. ## Try the preview We are opening a limited tech preview of the **Aletyx AI Assistant**. If your team works with decision models and you want to see how this feels in practice, request access to the limited tech preview. We are opening access gradually and would genuinely love to hear how people use it. [**Request Access**](https://aletyx.ai/contact/) ## FAQ **What is a business decision, and why does it matter in production systems?** A business decision is a committed choice that allocates resources between possible actions to achieve an outcome, often under uncertainty. In production, decisions must be consistent, explainable, and testable because they affect revenue, risk, and compliance. **What is Decision Intelligence, in practical terms?** Decision Intelligence (DI) is a discipline that advances decision making by explicitly understanding and engineering how decisions are made, and how outcomes are evaluated, managed, and improved via feedback. **What is a DMN decision model?** A DMN decision model is a standardized, executable way to represent decision logic, including policies, thresholds, eligibility rules, and exceptions. It helps teams keep business intent and system behavior aligned, and makes logic easier to review and test before release. **How does an AI assistant help with DMN decision models?** It helps teams understand complex models faster, propose changes from plain language, review for edge cases, and generate test scenarios for better coverage. Nothing changes automatically. Analysts stay in control and approve what is applied. ## 5 takeaways - Decision analysts understand policy changes first, but often can’t ship them. - DMN models live between business intent and technical implementation. - Technologies like Decision Control provide self-service governance tools to reduce ticket-driven bottlenecks. - An AI assistant adds a “second pair of eyes” for complex decision logic. - **Aletyx AI Assistant shifts the workflow from clicking through the model to a conversational with controlled suggested edits.** ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Architecting Intelligence Beyond LLMs Source: https://aletyx.ai/blog/architecting-intelligence-beyond-llms/ [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) [DMN](https://aletyx.ai/topics/dmn/) January 5, 2025 5 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published January 5, 2025 LLMs, GenAI, AgenticAI and similar topics are now on every content on your feed. Although, the push for AI adoption present a fundamental challenge for enterprise architects who seek: **How to balance AI innovation with the enterprise requirements for governance, explainability, and reliable execution of core business requirements?** The architectural decisions made today will determine whether AI initiatives deliver long-lasting business value or introduces new risks to the business, with accumulated minor errors and derived huge losses. In this article, we break down fundamental concepts to support a broader understanding of AI solutions, while focusing on two optimal architectural strategy for enterprise AI involves a strategic combination of Statistical AI and Symbolic AI, rather than a choice between them. And here’s how we’ll explore the topic: - Why LLMs and other predictive models, when used in isolation, may not fully address enterprise requirements - The distinct behaviors of probabilistic versus deterministic processing and their implications for enterprise systems - Strategic considerations for leveraging Statistical AI versus Symbolic AI in solution design - How to combine Symbolic AI with Statistical AI to create innovative and enterprise-ready solutions The success of an enterprise intelligent solution is determined by its architectural design. Ultimately, it comes down to how the underlying AI makes decisions—and the optimal strategy combines Statistical AI and Symbolic AI rather than choosing between them. ## The Two Concepts You Must Know About How AI Works Artificial Intelligence research is spread across multiple focus areas, exploring different methodologies and applications. And given the context of the article, we can narrow down the conversation to two main branches, and break it down into fundamental behavior characteristics. An intelligent system executes computational operations to transform inputs into meaningful outputs. **Here’s the secret to understanding AI:** ##### Symbolic AI (Deterministic) Operates based on explicit, pre-defined rules and logic. The same inputs consistently produce the same outputs, ensuring predictable and explainable behavior. ##### Statistical AI (Probabilistic) Learns patterns from large datasets and uses probability distributions to generate outcomes. Identical inputs might occasionally yield different results. Predictive models opened new opportunities to create amazing new user experiences, but as we know that there is no single solution to match every possible problem, we must consider what each type of AI is designed for, and their trade-offs. With that, we can either choose the best one for each problem, or even better – combine them and amplify their unique powers. ## The Power of Symbolic AI: Real-World Success Running side by side with Statistical AI (e.g. Generative AI), we have Symbolic AI with its deterministic reasoning approach. Symbolic AI is a well-established, proven way to enable intelligence in enterprise solutions, as demonstrated by the following real stories: - **Healthcare Billing Automation**: Over 50,000 daily billing decisions automated in hours, significantly reducing manual workload previously requiring more than 100 specialists. - **Rapid Rule Changes**: Business analysts update complex decision rules in mere hours (previously weeks), enabling instantaneous enhancements without costly retraining or downtime. - **Insurance Policy Processing**: Nearly 20,000 rules automated, reducing policy processing from 18 minutes to under 2 minutes, substantially enhancing operational efficiency and customer satisfaction. ## Architecting Intelligence: Combining Statistical and Symbolic AI At Aletyx, we don’t see GenAI and symbolic logic as competitors—they’re complementary tools: ### Generative AI Core strengths: Pattern recognition, content generation, prediction from existing data - Content generation - Conversational AI - Pattern recognition - Sentiment analysis - Exploratory analytics - Personalization and recommendations ### Symbolic AI Core strengths: Logical inference, explicit knowledge representation, consistency - Regulatory compliance - Auditing - Financial decision-making - Insurance claim automation - Healthcare policy validation - Complex pricing structures - Regulatory change management **Neurosymbolic AI:** Combines both for confidently predicting with the safety of rule-based guardrails The combination of both GenAI and Symbolic AI allows powerful applications of AI. To simplify the explanations, and given its native AI readiness, from now on, let’s use **Drools** as the reference implementation and technology for Symbolic AI. See some ways to approach this architectural combination: - **Separation of concerns: Analysis × Execution**: GenAI analyzes complex data scenarios + Drools execution of final decisions based on explicit, auditable rules. - **Guardrail Validations**: GenAI provides recommendations; Drools validates, consistently, these outcomes against pre-defined compliance and regulatory constraints. - **Confidence-based Fallback**: GenAI handles common, high-confidence scenarios, and automatically escalates decisions to Drools. Drools can automate human involvement based on the defined confidence thresholds. ## Key Takeaways We embrace AI, therefore, we shape experiences through technology that meets enterprise needs, with native AI features that drive innovation. The key to delivering control, consistency, explainability and trust when using generative AI is to maximize confidence and trust by bringing Symbolic AI to the scene. [Aletyx build of Drools](https://aletyx.ai/enterprise-drools/) is ready to connect with your favorite GenAI tool, for reliable compliance with business requirements. It allows you to deliver unique experiences infused with AI at every level. Key takeaways on Statistical and Symbolic AI: | | Statistical AI (Gen AI) | Symbolic AI (Drools) | | --- | --- | --- | | Foundation | Statistical models (probabilistic inference) | Explicit logical rules (symbolic AI) | | Execution Predictability | Variable outcomes each run | Consistent, repeatable outcomes | | Explainability | Opaque, requires external tools | Fully explainable and transparent logic | | Compliance Suitability | Limited due to unpredictability | Highly suitable due to precise, rule-based logic | Key differences between deterministic and predictive types of intelligent processing At Aletyx, we specialize in creating robust intelligent solutions, combining AI’s innovative potential with deterministic accuracy and compliance assurance. **Ready to confidently architect your intelligent future? [Let’s talk!](https://aletyx.ai/contact/)** ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Automatic DMN to LLM Integration with MCP: Exclusive Aletyx Feature for Enterprise AI Source: https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/ [Model Context Protocol](https://aletyx.ai/topics/model-context-protocol/) [DMN](https://aletyx.ai/topics/dmn/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) December 20, 2024 2 min ![A close-up of source code displayed on a laptop](https://aletyx.ai/_astro/laptop-with-code.CvW-e5mA_r3c9t.webp) Published December 20, 2024 Bringing AI into your enterprise is no longer just about innovation—**it’s about control, safety, and scale**. At **Aletyx**, we’re the first to offer **automatic integration between DMN (Decision Model and Notation) and LLMs (Large Language Models)** through the **Model Context Protocol (MCP)**—with **zero custom code** required. This powerful capability is **built into the Aletyx Enterprise Build of Drools** and enables your decision logic to be **AI-ready out of the box**. ## What This Means for You Whether you’re a **developer**, **architect**, or **CTO**, here’s what you gain: - **Plug-and-play GenAI integration** with your decision models - **No hallucinations, no fine-tuning, no risk** - **Full policy enforcement and auditability** Just **add the MCP dependency**, and your DMNs are automatically exposed as intelligent, policy-compliant AI agents—ready to be used by LLMs. --- ## How It Works With the **Aletyx Enterprise Build of Drools**, integrating DMNs with LLMs is as simple as: Add the **MCP protocol dependency** to your project Use **DMN models** as intelligent, context-aware agents Let the system handle the rest—**zero extra code needed** 🛠️ Note: Today, this automatic integration is available for **Spring Boot** projects. Support for **Quarkus** is coming! With Aletyx, your **DMN models act as the foundation of trust**—bringing structure, control, and policy enforcement into your GenAI. In other words: **DMN provides the guardrails LLMs need** to operate safely in your enterprise. --- ## What If You’re Using Open-Source Apache KIE? You can still integrate DMNs with LLMs using MCP, LangChain, or other frameworks—but you’ll need to do it manually: - Write your own integration layer - Handle context mapping and LLM interaction logic - Maintain and secure it on your own With Aletyx, you skip all that. It’s already built in. --- ## Ready to See It in Action? Whether you’re exploring GenAI, modernizing decision services, or looking to scale safely, Aletyx provides the fastest path forward. 👉 [Visit aletyx.ai](https://aletyx.ai/) to learn more 👉 Or [book a call](https://aletyx.ai/contact/) to see it live --- # Decision Tables: What They Look Like for Business Users Source: https://aletyx.ai/blog/decision-tables-for-business-users/ [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) [DMN](https://aletyx.ai/topics/dmn/) AI Assistant March 26, 2026 6 min ![A glowing light bulb on a dark wooden surface](https://aletyx.ai/_astro/glowing-light-bulb.BJiTEkAc_7nNi2.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published March 26, 2026 Every company has policies. Loan approval criteria. Claim routing logic. Pricing rules. Compliance checks. In most companies, policies live in someone’s head, a shared spreadsheet, or buried in application code. The problem isn’t complexity. It’s that the people who own the policy have no direct access to it. Every change means cross-team coordination and waiting. ## What is a decision table? A decision table is exactly what it sounds like. A table. Rows and columns. If you’ve used a spreadsheet, you already know how to read one. Each row is a rule. The columns on the left are the conditions. The columns on the right are the outcomes. That’s it. Here’s the simplest possible example. One condition, one result: | Credit Score | Risk Category | | --- | --- | | \> 750 | Low | | 680 - 750 | Medium | | < 680 | High | Three rules. That’s the policy. Not a description of the policy, not a requirements document for someone else to implement. The actual rule, ready to run. Now layer in more conditions. Same format, same clarity: | Credit Score | Debt-to-Income | Loan Amount | Decision | | --- | --- | --- | --- | | \> 720 | < 35% | Any | Approved | | 680 - 720 | < 40% | < $500K | Approved with conditions | | 680 - 720 | < 40% | \>= $500K | Referred to underwriter | | < 680 | Any | Any | Denied | More columns, more rules. The policy owner owns the table. When a regulation changes the threshold from 680 to 660, they change one cell. ## Why this matters Traditionally, this kind of logic ends up embedded in application code. The approval threshold, the debt-to-income cutoff, the routing logic… mixed in with database calls, error handling, logging, and technical plumbing. Not because anyone designed it that way, but because that’s how systems were built. When regulations change, updating logic takes cross-team effort and time, rather than allowing business teams to make changes directly. A decision table separates policy from code. It makes rules visible, testable, and easy to update. Engineers focus on the platform, not manual changes. ## What it looks like in practice We built a decision table experience inside Aletyx Decision Control that works exactly like this. You open it, and it looks like a spreadsheet. Because that’s the format people already think in. [Video: YouTube video](https://www.youtube.com/embed/wB6C-gIHapE) In this video, you can see the full cycle: start with an empty screen, define your decision logic in a familiar spreadsheet-like interface, and have a running decision service in under a minute. But here’s where it gets interesting. ## AI helps you build it Instead of manually entering every rule, you describe what you need in plain language. “Add a rule for applicants over 65 with income below $30K that routes to manual review.” The Aletyx AI Assistant modifies the table. You review the change, accept or adjust, and move on. It also generates test cases automatically, covering every condition in your table so you know it works before it goes live. Not some of the conditions. All of them. ## One-click publish Tools like Aletyx Decision Control let business users publish decision tables directly. One click makes it a live service for applications. No waiting for release cycles. The policy changed, it was tested, and it’s live. And under the hood? The decision table is fully compliant with DMN 1.6, an open industry standard. No vendor lock-in, no proprietary format. Your logic is portable and standards-based, but you never have to think about that. ## What changes when policy owners have direct access Instead of requirements documents that get translated into code that nobody can verify back against the original intent… the policy is authored directly. In a format that **is** the executable logic. When a regulation changes, the person who understands the regulation makes the update. Tests it. Publishes it. The audit trail shows exactly who changed what, when, and why. No translation layer. No lost intent. Everyone works on what they do best. ## Where this is going This is foundational. Decision tables that policy owners manage directly are powerful on their own. But as AI agents become part of how enterprises operate, these same decision tables can become the policies that govern what AI can and can’t do. The rules the AI must follow. More on that soon. For now, the starting point is simple: your business logic should be visible, testable, and owned by the people who understand it best. ## Try it yourself Aletyx Decision Control is available today. If your team manages business policies and wants a platform where the people who own the rules can author, test, and publish them directly, get started now. A tech preview of the AI Assistant and new Decision Table experience is open. Request access to try it and share feedback. [**Request Tech Preview Access**](https://aletyx.ai/contact/) [**Get Started with Decision Control**](https://aletyx.ai/free-trial/) ## Key Takeaways - A decision table is a simple table of rules: conditions on the left, outcomes on the right. If you can read a spreadsheet, you can read a decision table. - Decision tables separate business policy from application code, making rules visible, testable, and changeable without a release cycle. - AI can accelerate authoring: describe what you need in plain language, and the Aletyx AI Assistant builds and tests the table for you. - Decision tables built on DMN 1.6 are standards-based and portable, with no vendor lock-in. - As AI agents enter the enterprise, decision tables can become the policies that govern what AI can and can’t do. ## FAQ ### Do I need to know DMN to use a decision table? No. DMN 1.6 is the open standard running under the hood, but you never have to interact with it directly. The experience looks and feels like a spreadsheet. ### Can decision tables handle complex logic, not just simple lookups? Yes. Decision tables scale from a single condition with three rules to dozens of conditions with hundreds of rules. The format stays the same. You can also combine multiple decision tables together for more complex scenarios. ### How is this different from managing rules in a spreadsheet? A spreadsheet is a document. A decision table in Aletyx Decision Control is executable. You author it, test it, and publish it as a live service. It runs. A spreadsheet just sits there until someone manually translates it into code. ### What happens to my existing business logic in code? Decision tables don’t require ripping out existing systems. They can run alongside your current applications, gradually taking over the policy logic that today lives in code. Engineers keep the architecture, and the policy moves to where it belongs. ### Who typically authors decision tables? Business analysts, policy owners, compliance teams, and domain experts. Anyone who understands the business rule. The Aletyx AI Assistant helps with authoring and test generation, so the barrier to getting started is very low. ### Is this only for financial services? No. Any industry with business policies benefits from decision tables. Healthcare, insurance, manufacturing, retail, government. Anywhere a decision needs to be consistent, explainable, and auditable. ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Essential Concepts for Navigating Enterprise AI Trends Source: https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/ [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Model Context Protocol](https://aletyx.ai/topics/model-context-protocol/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) January 15, 2025 8 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published January 15, 2025 Since the 1970s, Artificial Intelligence (AI) has evolved through multiple phases, from niche academic research to a strategic imperative reshaping industries worldwide. As of 2025, AI is no longer a futuristic concept but a business necessity, driving innovation, efficiency, and competitive advantage across sectors. For companies just beginning their AI journey, grasping the foundational concepts and current landscape is critical to unlocking AI’s transformative potential. To understand how to unlock the power of AI, let’s start by going through basic concepts. For learning purposes, we can reduce the scope to commonly used buzzwords, offering you clarity on what are their characteristics. After you finish exploring the fundamental concepts and get a better understanding of AI’s common concepts, your next step is to become aware of the [common challenges of enterprise adoption of AI, and understand how to overcome them by strategically use different AI systems](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/) and not having to choose between them. ## What Is AI and Why Is It Different Now? Artificial Intelligence refers to systems or software capable of performing tasks that typically require human intelligence, covering abilities such as learning, reasoning, problem-solving, perception, and language understanding. Although AI research dates back to the 1950s, recent leaps in computing power, data availability, and algorithmic sophistication, especially in the area of deep learning, have dramatically accelerated its evolution. Today, AI is a powerful tool for expanding human creativity and productivity. In enterprises, it enables automation of complex operations, accelerates decision-making, and allows offering uniquely personalized customer experiences at scale. However, most enterprises still struggle balancing AI innovation with the enterprise requirements for governance, explainability, and reliable execution of core business requirements. **TIP:** The architectural decisions made today will determine whether AI initiatives deliver long-lasting business value or introduces new risks to the business, with accumulated minor errors and derived huge losses. Deciding what is the best possible strategy, tool and way to innovate using AI, is a complex task. We can reduce the AI vast landscape to a smaller scope of commonly used terms trending across enterprises, and introduce each concept with its surrounding context. We’ll also break down the concepts involved in the overall steps of the decision making throughout this and future articles. ## Breaking Down AI Essential Concepts: AI/ML, GenAI, Agentic AI, LLMs, Symbolic AI **Symbolic AI** has been largely used across the industry for many years, and stands as a solid enterprise approach for tackling needs that range from simple to complex mission-critical requirements. It’s based on programming systems with explicit rules and logic to perform tasks. This method has been working well and targets clearly defined requirements seeking assurance of predictable results, transparency and governance. However, it was not designed to handle ambiguous, unstructured, or high-dimensional problems that require learning from vast amounts of data. As technology advanced, other Artificial Intelligence (AI) research fields brought us systems that could learn from data rather than relying solely on predefined rules. Within this space, **Machine Learning (ML)** was quickly perceived by its powerful technique that unlocked computers’ ability to self-improve, by identifying patterns in large datasets. These patterns gave them probabilistic abilities to predict or classify, without being explicitly programmed for every scenario. **Note:** Until this point, AI/ML was not mainstream as it required different areas of expertise, computing power and involved other concerns that were usually enough to slow down its adoption. However, it was the key enabler of a new branch of AI that disrupted the market. **Generative AI (GenAI)** is a branch of AI that uses machine learning models to create new, original content based on learned data patterns models are designed to create new content. It can create text, images, music, or other digital artifacts based on patterns learned from vast amounts of data. Unlike traditional analysis or classifications done by AI/ML, GenAI generates original outputs when given specific instructions or **prompts**. Here’s how it works: The input is a **prompt**, instructions describing what the GenAI solution is expected to generate. Prompts can bring guidance on the generation to some degree. Think of it as the question you ask **ChatGPT**, **Gemini** or **Claude**. The **GenAI** model processes the prompt and using its learned knowledge, generates a relevant response, predicting word after word based on probabilities. **TIP:** At the core of many generative AI systems are Large Language Models (LLMs). These are massive neural networks trained on enormous amounts of text data from books, websites, and conversations. LLMs learn statistical relationships between words and phrases, enabling them to predict what comes next in a sentence or generate coherent paragraphs on a wide range of topics, being capable of producing human-like language without explicit programming for each task. For example, if you give a **generative AI** a prompt like “write a poem about the ocean”, the quality and clarity of the prompt heavily shapes the quality of the output. As generative solutions were used by more and more people, the concept of **prompt engineering** became the next “big thing” in terms of career, since GenAI was now becoming naturally used to increase productivity and accelerate businesses. **Prompt engineering** refers to the practice of crafting prompts that effectively guides generative models in creating customized, polished responses that are closer to expected results. It ultimately was a way to seek answers that were factual, useful, relevant or even, to control the results. While GenAI systems require inputs to operate, **Agentic AI** takes it a step further. An AI Agent is a system that can act autonomously. It is aware of its environment and data, and without any external intervention, it sets goals, makes decisions, and executes one or a series of tasks required to achieve a particular goal. All with minimal human intervention. Here’s an example to clarify the concept of an **AI Agent**: Imagine working with an assistant (but a digital one) that not only answers your questions, it understands when and how to schedule meetings, address straightforward questions you receive via email, automatically replying them without your involvement, ordering supplies, and adapting its prioritized tasks on its own. Such an advanced behavior, requires a pre-existing set of systems and APIs, acting at some level, as an orchestrator. Having this clearly defined set of “possibilities” made available through integration endpoints, agents can act as an independent figure and pursue objectives. Additionally, what makes this possible, is the system’s ability to learn, reason, plan, and interact with humans and external systems, efficiently operating on every data exchanged. With the rise of AI Agents and GenAI, the need to make systems available to AI systems became latent. Aiming to avoid vendor lock-in and create standard ways to interact with external tools, the **Model Context Protocol (MCP)** was created and quickly got traction. **MCP** defines a standard method for systems integration with AI. For an AI agent to perform a task like booking a meeting, it needs to know what’s available to be used, and have structured and permissioned access to the relevant API. In addition to transparency, this standardization accelerates developers with common and simple ways to augment systems and to consider using guardrails to mitigate potential risks of AI hallucination. ## Overcoming Challenges: Enterprise Path to Intelligent Solutions Risks of financial losses, regulatory exposure, brand damage, and flawed operations, are some of the concerns regarding AI innovation, especially in enterprise software. Such risks are imminent when a company opens space to a possible lack of compliance with business policies or governance standards. **To avoid common pitfalls in Enterprise AI adoption**, here’s what you need to know before engaging on your next effort with AI: [Overcoming Challenges: Enterprise Path to Intelligent Solutions](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/). Understand the risks and limitations of intelligent systems, their potential impact on enterprise organizations, and most importantly, how to overcome each limitation without giving up on trust, compliance, transparency and control, and skipping the tough process of making a choice between different AI options. ## Key Concepts Summary **Symbolic AI**: AI based on explicit rules and logic, designed for clear, explainable reasoning in well-defined domains. **Artificial Intelligence (AI) / Machine Learning (ML)**: AI is the broad field of creating intelligent systems; ML is a subset where machines learn patterns from data to make predictions or decisions. **Generative AI (GenAI)**: A branch of AI that creates new, original content (text, images, music) based on learned data patterns. **Prompt**: The input or instruction given to a generative AI model to guide content creation. **Large Language Models (LLMs)**: Massive AI models trained on extensive text data, capable of understanding and generating human-like language. **Agentic AI**: Autonomous AI systems that perceive, plan, decide, and act independently to achieve complex goals. --- *Need help on getting where you want to be in this intelligent automation journey? [Tell us more about your challenges, we’re here to help.](https://aletyx.ai/contact/)* ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # The Missing Manual for Kogito: How to Use Java APIs Instead of Auto-Generated REST Endpoints Source: https://aletyx.ai/blog/how-to-use-java-apis-with-kogito-process/ Enterprise Enablement [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Kogito](https://aletyx.ai/topics/kogito/) December 28, 2024 3 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published December 28, 2024 > If you’ve been exploring Apache KIE and Kogito to build BPMN workflows, you’ve probably seen the slick domain-specific REST endpoints or Kafka listeners that “just work” out of the box. Sounds great, right? Until you realize: - You want custom logic before starting a process - You don’t want a bunch of auto-generated REST endpoints cluttering your app - You’re calling from another Java service and REST feels like overkill - Or worse: you turned off codegen and… now what? ## Here’s the part nobody explains: how to use the **Java API directly.** *And that you won’t find this in the docs. And if you do, it’s probably broken.* Spoiler: it *is* possible. But there’s almost no guidance, and most examples are outdated or simply wrong. Let’s fix that. --- ## Why You Might Not Want Auto-Generated REST By default, Kogito generates REST endpoints for every BPMN process you define. For example, if you have a Hiring process, you’ll get: ``` POST /hiring GET /hiring/{id} DELETE /hiring/{id} ``` This is great for prototyping or exposing workflows as services. But what if: - You want to kick off the process from within a service call? - You need to transform or validate input before instantiating the process? - You need tight control over how and when your process runs? That’s when you reach for the Java API. --- ## Step-by-Step: Starting a Kogito BPMN Process with Java Let’s walk through a real-world example of triggering a process without using the generated REST endpoint. ### ✅ Step 1: Disable the auto-generated REST Add this to your application.properties to opt out of codegen: ``` kogito.generate.rest=false ``` Kogito will skip generating REST endpoints for your processes. ### ✅ Step 2: Inject and trigger the process programmatically Use CDI and the ProcessService API to interact directly with your process: ``` import java.util.HashMap; import java.util.Map; import org.kie.kogito.Model; import org.kie.kogito.process.Process; import org.kie.kogito.process.ProcessInstance; import org.kie.kogito.process.ProcessService; import jakarta.enterprise.context.ApplicationScoped; import jakarta.inject.Inject; import jakarta.inject.Named; @ApplicationScoped public class MyService { @Inject ProcessService processService; @Inject @Named("contentApproval") // This must match your BPMN process ID Process process; public void startMyProcessCustomWay() { Model model = process.createModel(); Map variables = new HashMap<>(); //document is an input process variable variables.put("document", new Document("id", "name", "content")); model.fromMap(variables); ProcessInstance instance = processService.createProcessInstance( (Process) process, null, model, null, null); System.out.println("Status: " + instance.checkError().variables()); } } ``` > 💡 **Pro tip**: The @Named(”…”) annotation must match the id attribute in your BPMN file — not just the filename. --- ## Now You’re Free to Build Real Applications This pattern gives you full control over how and when your workflows are triggered: - ✅ Call from another Java service - ✅ Add custom validation, authentication, or logging - ✅ Coordinate with other systems before starting a process - ✅ Avoid exposing sensitive internal processes via REST ## What About Kafka Listeners? Same deal. If you were relying on generated Kafka listeners but need something custom, just disable the codegen and wire up your own event handling logic. We’ll cover that in a future post — follow us on [LinkedIn](https://www.linkedin.com/company/aletyx) or [X](https://twitter.com/aletyxai) so you don’t miss it. --- ## Final Thoughts This kind of low-level access is critical in enterprise environments — especially when architectural constraints or integration requirements are non-negotiable. At [Aletyx](https://aletyx.ai/), we talk to teams that love the [power of Kogito](https://aletyx.ai/intelligent-process-automation/) but need more than “click-to-run” demos. That’s why our enterprise build supports these patterns — and more — out of the box. We’re sharing what works. No fluff. No broken tutorials. 🔗 **Got questions?** Reach out via our [contact page](https://aletyx.ai/contact/). ## ❤️ Was this helpful? Give it a share. You might just save another developer from a week of trial-and-error. ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Overcoming Challenges: Enterprise Path to Intelligent Solutions Source: https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/ [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) [Governance & Compliance](https://aletyx.ai/topics/governance-and-compliance/) January 10, 2025 4 min ![A glowing light bulb on a dark wooden surface](https://aletyx.ai/_astro/glowing-light-bulb.BJiTEkAc_7nNi2.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published January 10, 2025 Why are intelligent systems often associated with lack of compliance? Unpack the trade-offs derived from the characteristics of the types of AI systems and explore a potential path to overcome challenging limitations for enterprise adoption. After breaking down fundamental concepts and with a broader understanding of AI solutions, you’ll understand the challenges of AI adoption within enterprise environments, and how to strategically combine different AI approaches, instead of choosing between them. > To unlock the power of AI and understand essential concepts and commonly used buzzwords within the AI landscape, refer to the first post of this series, [Essential Concepts for Navigating Enterprise AI Trends](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/). Risks of financial losses, regulatory exposure, brand damage, and flawed operations, are some of the concerns regarding AI innovation, especially in enterprise software. Such risks are imminent when a company opens space to a possible lack of compliance with business policies or governance standards. Understanding the reason why these risks exist, and how to overcome such limitations and challenges, is the next step, as it opens doors for confidently discussing and driving core systems modernization and AI-driven innovation. ## AI in Enterprise Systems: Limitations and Risks Why would intelligent systems be associated with lack of compliance, you may think. Let’s unpack the trade-offs derived from the characteristics of the types of AI systems, and then, explore a potential path to overcome challenging limitations. **NOTE:** As Generative AI adoption is skyrocketing, let’s limit the scope of this article for learning purposes. If you are interested in learning more about other systems, please let us know. Share your areas of interest, topics or questions you’d like to hear more about! AI systems based on statistical predictions, such as Generative AI, can drive disruptive innovation. However, when used indiscriminately, can lead to: - Factors of unpredictability, and inconsistent processes for decision-making - Unexpected outcomes derived from hallucination. - Inability to ensure repeatable results from a same given set of inputs - Inability to justify how a decision was made or why a particular response was given. *Every* technology has trade-offs, and software architecture plays a special role in addressing pain points. Let’s understand how. ## Overcoming Trade-offs and Driving Enterprise AI-Innovation There’s no need to avoid GenAI and other statistical AI systems. The solution relies on how it is adopted, and which strategies are available to ensure enterprise-grade compliance and predictability. When tracking which applications would benefit from AI innovation, a cautious analysis should determine which of these applications are core to the business functioning. In other words, there should be a clear understanding of which are the functionalities and associated systems that drive core business operations, that directly involve business logic. As an example, a discount service, or a loan approval service, are examples of solutions that wouldn’t benefit from lack of control and unpredictability. **TIP:** To learn more about the types of AI and their associated outcomes and use cases, check out [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/). So how do you safely adopt AI in such a case? How to overcome the unpredictability of GenAI or the lack of trust on Agentic AI decision-making? By designing intelligent solutions that rely on Guardrails, it’s possible to leverage the best out of GenAI and Agentic AI, while ensuring policy compliance and trusted autonomous operations. **Hybrid Intelligence combines:** - **the transparency and control of Symbolic AI,** - **with the creative and generative capabilities of GenAI,** - **and the autonomy and adaptability of Agentic AI.** When exploring the basic concepts, Symbolic AI was presented as being designed to drive efficient execution of reasoning and drive predictable results. Therefore, it fits perfectly as guardrails, the safety net for AI generation, as it can ensure predictable outcomes for operations that demand precision and high levels of control over its reasoning. --- To see a practical hands-on demonstration of how a discount policy sample would work when combining GenAI, like Claude, and Symbolic AI, such as Aletyx build of Drools, check out this short video: [Video: Hybrid Intelligence Demo](https://www.youtube.com/embed/t-RqnSpXN5E) By having a combination of intelligent systems, not only GenAI experience can be significantly improved within enterprise solutions; The level of trust and flexibility offered to AI agents unlocks a higher level of autonomy, where decision-making processes can happen with confidence. --- What’s holding you back from confidently architect your intelligent future? [We can help.](https://aletyx.ai/contact/) ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Enabling Teams with Apache KIE 10: Aletyx's Workshop on Kogito-based Workflows Source: https://aletyx.ai/case-studies/aletyx-workshop-kogito/ Enterprise Enablement [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Kogito](https://aletyx.ai/topics/kogito/) February 18, 2025 2 min ![A close-up of source code displayed on a laptop](https://aletyx.ai/_astro/laptop-with-code.CvW-e5mA_r3c9t.webp) By [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Published February 18, 2025 As part of our enablement offerings, Aletyx recently delivered our **Apache KIE 10 Workshop** to a customer in the science and technology sector. This workshop, one of Aletyx’s core training programs, is designed to help development teams gain hands-on experience with **Kogito based workflows** and understand how to effectively apply the technology in real-world environments. ### Built for Practical Adoption The Aletyx KIE 10 Workshop is structured to take participants from foundational concepts to production-ready practices. It combines guided instruction with hands-on labs, and includes exclusive content developed by Aletyx to bridge the gap between learning and real implementation. Core topics covered in the workshop included: - **Environment & Dev Setup Across Platforms** Step-by-step guidance to configure Java, Git, containers, cloud tools, and Visual Studio Code---enabling consistent environments across diverse teams. - **Modeling Decisions and Rules** Introduction to **DMN** and **DRL**, with exercises to build and deploy decision services using the **KIE Sandbox**. Labs covered both low-code modeling and rule-based logic development. - **Kogito Workflow Foundations** Key concepts around the **workflow engine, runtimes, job service, user task handling**, and orchestration patterns like **SAGA** and **Four Eyes approval**. - **Kogito Java APIs** Beyond auto-generated REST endpoints, the workshop includes **how to work directly with Kogito Java APIs**, providing developers with more control and flexibility in application design. - **Customization & Accelerators** Attendees learned how to tailor the **KIE Sandbox** to their needs and apply **accelerators** to streamline decision modeling and deployment workflows. - **Advanced Workflow Topics** Topics such as **event-driven architecture with Kafka, GraphQL integration**, and **various subprocess patterns** (embedded, reusable, ad-hoc, and event-based) helped teams explore advanced use cases. ### Supporting Distributed Teams With the customer’s teams spread across multiple regions, the workshop was delivered in a format that supports remote collaboration and asynchronous participation. The combination of structured labs and production-focused content gave every participant a practical path forward---regardless of geography. --- The Apache KIE 10 Workshop is just one example of how Aletyx equips teams with the skills and confidence to build intelligent automation solutions using modern tools like **Kogito**. If you’re looking to up-skill your team or plan a broader enablement initiative, get in touch---we’re here to help. ## About the author [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Co-founder & CCO More than 15 years putting rules, process, and AI to work where enterprise decisions matter. Focused on automation organizations can defend, not just deploy. [More from Tim](https://aletyx.ai/authors/tim-wuthenow/) --- # Don't hire consultants. Hire the architects Source: https://aletyx.ai/consulting/ Specialized professional services Your automation infrastructure is too critical for generalists. Partner directly with the founding engineers of Drools and jBPM to solve your toughest architectural challenges. [Book an Architecture Review](https://aletyx.ai/contact/) [See Our Expertise](https://aletyx.ai/consulting/#expertise) ## "Generalist" advice is creating your technical debt Most System Integrators treat Intelligent Automation like just another application. They build brittle architectures, introduce anti-patterns, and leave you with a system that creates more problems than it solves. ### Performance Bottlenecks Caused by poor Business Rules design. ### Migration Nightmares Caused by deep coupling with legacy frameworks. ### Scalability Walls Caused by treating stateful processes like stateless services. Stop guessing. Bring in the team that built the engine. ### Modernization & Migration Escape the Legacy Trap. We don't just "lift and shift." We re-platform. - **BM/Red Hat Migration:** Move off EOL platforms (BAMOE/PAM) to Aletyx without rewriting business logic. - **Cloud-Native Transition:** Refactor monolithic implementations into scalable microservices on Kubernetes. [Book an Architecture Review](https://aletyx.ai/contact/) ### Performance Rescue For when "slow" becomes "unacceptable." When your rules take seconds instead of milliseconds, you need a deep-dive investigation. - **Algorithm Analysis:** We profile your execution path to eliminate redundancy. - **Memory Leak Detection:** Identify and fix state management issues in long-running JVMs. [Book an Architecture Review](https://aletyx.ai/contact/) ### Hybrid AI Architecture Build the "Brain" of your Agentic AI. Don't let your Data Science team build AI in a silo. We help you integrate Generative AI with your existing Intelligent Automation Services. - **MCP Implementation:** Expose your Drools logic as tools for LLMs. - **Guardrails Design:** Architect the safety layer that prevents AI hallucinations in production. [Book an Architecture Review](https://aletyx.ai/contact/) ## We are not a "body shop". We are specialized ops We do not sell "hours." We sell outcomes. Unlike traditional consultancies that want to embed 20 developers in your office for years, our goal is to fix the problem, transfer the knowledge, and let you fly. ### Audit & Roadmap (2-4 Weeks) A rapid, high-impact assessment of your current stack with a clear remediation plan. ### Project Acceleration (3-6 Months) Embedded experts to unblock critical initiatives and mentor your lead engineers. ### Strategic Advisory (Retainer) A "Red Phone" direct line to our core architects for on-demand guidance. Stop guessing. Bring in the team that built the engine. Criteria Traditional System Integrators Aletyx Engineering Services The Team "B-Team" Generalists (Junior/Mid developers learning on the job) The "A-Team" (Principal Engineers & Core Contributors) Knowledge Source Google & StackOverflow (They read the documentation) Source Code & Internals (We wrote the documentation) Incentive Model Billable Hours (Profit from extending the problem) Speed to Resolution (Profit from fixing it fast) Legacy Approach "Lift and Shift" (Move the mess to the cloud) "Refactor & Optimize" (Fix the architecture) End State Vendor Dependency Knowledge Transfer Criteria ### The Team Aletyx Engineering Services"Butts in seats" (Junior/Mid) Traditional System Integrators Staffing Model Criteria ### Knowledge Source Aletyx Engineering Services Reads the Documentation Traditional System Integrators Knowledge Source Criteria ### Incentive Model Aletyx Engineering Services Maximizing Billable Hours Traditional System Integrators Focus Criteria ### Legacy Approach Aletyx Engineering Services"Patch and Pray" Traditional System Integrators Solution Criteria ### End State Aletyx Engineering Services Knowledge Transfer Traditional System Integrators Vendor Dependency Your last chance ## Solve the "unsolvable" problem If your current partners are stuck, it's time to call the creators. [Contact Engineering Sales](https://aletyx.ai/contact/) Direct discussion with a technical lead, not a sales rep. --- # Move Proven Decisions to Production—With Control. Source: https://aletyx.ai/decision-control-tower/ Decision Control Tower Decision Control Tower is the governance layer around Decision Control. Your teams keep authoring and testing; Tower controls who can promote which version, through which workflow, and into which environment. [See Tower in Action](https://aletyx.ai/contact/) [Explore Decision Control](https://aletyx.ai/decision-control/) Custom promotion workflows OIDC-backed access Accountable human approvals ![Decision Control Tower task showing Development to Production, requester context, a dark approval workflow, and the authorized action](https://aletyx.ai/_astro/tower-task-hero-dark.DJmaQ7QA_Z1XAbyx.webp) Governed Release Path ## One Version. One Explicit Path to Production. Define where decisions run, request a specific version, route it through the workflow your organization requires, and keep the release context with the promotion. 1. 01 **Define** Name environments and control who may reach them. 2. 02 **Request** Choose the version, route, workflow, and required context. 3. 03 **Review** Assign accountable human tasks and authorized actions. 4. 04 **Promote** Move the approved version and keep its release record. Environment Boundaries ## Make the Release Path Explicit. Define and classify environments such as Development and Production, monitor their status, and make every source-to-target promotion visible. Connect any standards-compliant OpenID Connect provider and apply role-based access to the environments and governance actions each user may reach. ![Development and Production environment cards showing online status and classification tags](https://aletyx.ai/_astro/tower-environments-focus.Dbtk4d6Z_Z1NHdMI.webp) Policy-Defined Promotion ## Turn Governance Policy Into a Workflow. Use a custom promotion workflow—not a fixed approval form. Choose the source, target, version, and workflow; require context such as a business justification; and model change requests, human review, approval, and automated promotion steps. ![Dark custom workflow with change request, approval, promotion, and required process input](https://aletyx.ai/_astro/tower-workflow-focus-dark.B0VGpN9I_oqCbR.webp) Release Traceability ## Keep the Release Record With the Version. Follow each promotion from request through its current workflow state. Keep the model version, source and target environments, requester, justification, workflow, promotion ID, and related task context together in one reviewable record. ![Promotion details showing version, environment path, dark approval workflow, and promotion state](https://aletyx.ai/_astro/control-tower-promotion-dark.CO-9NrNU_Z1cWCha.webp) ## IT Stays in Control. Analysts Stay Autonomous. RBAC. Approvals. Promotion. Traceability — owned by IT. Decision Control Tower is where IT defines the rules of engagement. Analysts author and publish freely within the boundaries IT sets — and nothing reaches production without passing through IT-defined governance. ### RBAC IT defines granular permissions for authors, reviewers, and approvers. Every action in Decision Control respects the roles and policies IT establishes. ### Approval Workflows IT defines promotion controls. Decision changes move dev → test → prod only after passing IT-approved gates. No unreviewed changes reach production. ### Full Traceability Who changed what, who approved it, when it was promoted. Immutable logs. Exportable for regulatory review. ### Multi-Environment Promotion Managed flow across environments. Instant rollback. Change notifications at every stage. ### Git Integration Version synchronization with your repositories. Governed change management that fits your DevOps. ### Governance Dashboard Promotion status, pending approvals, environment health — all decision assets, all environments. [See It in Action](https://aletyx.ai/free-trial/) Frequently Asked Questions ## Clear answers about governed promotion. [Talk to Our Team](https://aletyx.ai/contact/) 01 What is the difference between Decision Control and Decision Control Tower? Decision Control is where teams author, evaluate, test, and publish decision models. Decision Control Tower governs how approved versions move between managed environments and who can act on those promotions. 02 Does Tower replace our identity provider? No. Tower authenticates through standards-compliant OpenID Connect providers. Provider-specific claims, groups, and role mappings are configured for your deployment. 03 Can we customize the promotion process? Yes. Promotion requests run through configured workflows that can include required inputs, human approval, change requests, and automated promotion steps. 04 How does role-based access affect approvals? Roles determine which environments, promotions, tasks, and actions a user may access. Authorized reviewers can claim governance tasks and take the actions permitted by the workflow. 05 What information accompanies a review task? A task can present the decision model and version, source and target environments, requester, justification, workflow context, and the available review action. 06 What evidence is retained for a promotion? Tower keeps the promotion context together: model and version, environment path, requester, justification, workflow, status, identifiers, and related task activity. 07 Can we manage more than Development and Production? Tower models named deployment environments and explicit promotion paths. The environment structure can reflect the stages used by your organization. 08 Does Tower change the decision logic? No. Decision logic remains owned and tested in Decision Control. Tower governs the release process around the resulting version. Governance for the Real Release Path ## Turn One Promotion Policy Into a Working Control Flow. Bring your environment model, approval rules, and identity provider. We’ll map one decision service from development to production in Decision Control Tower. [See Tower in Action](https://aletyx.ai/contact/) [Explore Decision Control](https://aletyx.ai/decision-control/) Start with one decision service, one promotion route, and the roles already used by your organization. --- # Turn Policy Into a Proven Decision Service. Source: https://aletyx.ai/decision-control/ Built by original Drools team members Model decisions visually, inspect live values, review every AI change, protect expected outcomes with reusable tests, and publish for people, systems, and agents. [See Decision Control in Action](https://dc-trial.aletyx.ai/) [Talk to Our Team](https://aletyx.ai/contact/) Visual DMN authoring Reviewable AI changes Test evidence before publish ![Aletyx Decision Control showing a loan pre-qualification decision model](https://aletyx.ai/_astro/aletyx-decision-intelligence-experience-3d.DVS5lhbO_Z2qG3V6.webp) One Governed Workspace ## The Model, Tests, and Runtime Stay Together Author the model. Run it against real inputs. Inspect values in place. Review AI-generated changes. Protect expected outcomes with test scenarios. Publish with the results in view. Then expose the decision to applications and agents—and trace every execution. 1. 01 **Author** Model policy visually in DMN. 2. 02 **Debug** Inspect the value behind every result. 3. 03 **Review** See and approve each AI-proposed edit. 4. 04 **Prove** Pin expected outcomes and rerun them. 5. 05 **Publish** Release with test evidence in view. 6. 06 **Operate** Serve agents and trace every execution. Live Evaluation ## See the Values Behind the Result Run a scenario beside the model, then hover inputs and intermediate expressions to see the values used in that evaluation. Evaluation highlights reveal the path while the output panel shows every evaluated decision. ![Decision Control showing the live value 10000 over the evaluated monthly-income expression](https://aletyx.ai/_astro/live-debug-focus.ByZX7_cH_ZRfROA.webp) AI-Assisted Authoring ## AI Drafts the Change. You Approve It. Ask the Assistant to update the model in plain language. Decision Control marks every proposed edit and shows the previous and new value, so you can accept or revert changes individually before moving on. [Explore AI Assistant](https://aletyx.ai/ai-assistant/) ![Aletyx AI Assistant change request with a reviewable before-and-after decision diff](https://aletyx.ai/_astro/aletyx-card-02-ai-drafts-you-approve._HNT1HLE_2eCSio.webp) Regression Protection ## Pin the Outcomes That Must Not Change Mark important outputs as expected, add scenarios to a test table, and rerun them after an edit. Matches stay green; a difference shows the expected and actual value at the field and scenario level. ![Decision Control regression test table with matching and differing outcomes](https://aletyx.ai/_astro/regression-tests-table.Cz-VGjYF_1UUEy.webp) Verified Publish ## Publish With the Test Evidence in Front of You When you publish, Decision Control checks the model's test scenarios and presents the result first. If one fails, it shows the exact mismatch and nothing has been published yet. Cancel to fix it—or explicitly choose Publish Anyway. ![Decision Control publish confirmation showing the exact expected and actual result for a failed test](https://aletyx.ai/_astro/verified-publish-focus.brxdxehh_dgC9T.webp) Agent-Ready Decisions ## Turn a Published Decision Into an Agent-Ready Skill Generate a SKILL.md from the governed decision model with its purpose, scope, required inputs, endpoint, and invocation instructions. Share the Agent Skill URL or download the bundle so an agent can discover and call the decision correctly. ![Active Agent Skill URL and generated SKILL.md for the loan pre-qualification decision](https://aletyx.ai/_astro/agent-ready-skill.CNMTbpTc_Z1pwFQ7.webp) Execution Evidence ## Trace Every Outcome to the Exact Model Version Open an execution record to see its status, timestamp, model version and hash, inputs, and outputs. Use the simulator to replay the case against another model version and understand what would change. ![Decision Control monitoring detail layered over a successful execution list](https://aletyx.ai/_astro/aletyx-card-04-trace-every-outcome.B0wyNqeK_Z1zezAC.webp) Decision Control Tower ## Analyst Autonomy. Enterprise Boundaries. Decision Control gives policy owners a fast visual workspace. Tower adds the operating controls around it—without forcing analysts back into ticket queues. - **Roles and approvals:** Define who can author, review, approve, and promote. - **Environment promotion:** Move governed versions across development, test, and production. - **Release evidence:** Connect every change, justification, approval, and deployment event. [Explore Decision Control Tower](https://aletyx.ai/decision-control-tower/) ![Decision Control Tower promotion details showing Development to Production, release metadata, and a dark-mode approval workflow](https://aletyx.ai/_astro/control-tower-promotion-dark.CO-9NrNU_Z176aIg.webp) ## A Decision Editor Is Not a Decision Lifecycle Capability Aletyx Decision Control BAMOE Canvas KIE Sandbox Visual authoring and live runner DMN authoring with form and table evaluation Visual DMN authoring with DMN Runner Visual DMN authoring and community tooling Live evaluation insight Evaluation highlights and hover values in the model Live inputs and outputs in DMN Runner Runner capabilities vary by tool AI-assisted model changes Built-in before and after diff with accept or revert Separate or custom workflow Separate or custom workflow Reusable expected outcomes Pin outputs with field-level match and difference states Runner scenarios and separate test tooling SCESIM and developer test tooling Publish verification Scenario summary before publish with explicit override Deployment through project tooling Deployment outside the editor Agent-ready delivery Generated SKILL.md and Agent Skill URL Not built into Canvas Not built into Sandbox Execution evidence Inputs, outputs, version, hash, simulation and replay Separate runtime and management tooling Separate runtime and management tooling Capability ### Visual authoring and live runner Aletyx Decision Control DMN authoring with form and table evaluation BAMOE Canvas Visual DMN authoring with DMN Runner KIE Sandbox Visual DMN authoring and community tooling Capability ### Live evaluation insight Aletyx Decision Control Evaluation highlights and hover values in the model BAMOE Canvas Live inputs and outputs in DMN Runner KIE Sandbox Runner capabilities vary by tool Capability ### AI-assisted model changes Aletyx Decision Control Built-in before and after diff with accept or revert BAMOE Canvas Separate or custom workflow KIE Sandbox Separate or custom workflow Capability ### Reusable expected outcomes Aletyx Decision Control Pin outputs with field-level match and difference states BAMOE Canvas Runner scenarios and separate test tooling KIE Sandbox SCESIM and developer test tooling Capability ### Publish verification Aletyx Decision Control Scenario summary before publish with explicit override BAMOE Canvas Deployment through project tooling KIE Sandbox Deployment outside the editor Capability ### Agent-ready delivery Aletyx Decision Control Generated SKILL.md and Agent Skill URL BAMOE Canvas Not built into Canvas KIE Sandbox Not built into Sandbox Capability ### Execution evidence Aletyx Decision Control Inputs, outputs, version, hash, simulation and replay BAMOE Canvas Separate runtime and management tooling KIE Sandbox Separate runtime and management tooling [Get a detailed migration assessment](https://aletyx.ai/free-trial/) Frequently Asked Questions ## Clear answers to your questions. [Start My Free 60-Day Evaluation](https://aletyx.ai/free-trial/) 01 Do analysts need Java or a local development environment? No. Decision Control provides visual DMN authoring, live evaluation, test scenarios, and publishing in the browser. Technical teams can manage the surrounding runtime and enterprise governance through Decision Control Tower. 02 How does the AI Assistant change a model? Describe the requested change in natural language. The Assistant proposes edits in the model, and Decision Control shows each changed cell with its previous and new value. You can accept or revert changes before moving on. 03 What are pinned test outputs? A pinned output is an expected result for a scenario. When you rerun the test set, Decision Control compares the current result with the pinned value and marks each output as matching or differing. 04 What happens if a test fails during publishing? Failed scenarios interrupt the publish flow and display the exact mismatch before anything is published. You can cancel and fix the model or explicitly choose Publish Anyway. 05 How do agents use a published decision? Generate a SKILL.md from the decision model, then share its Agent Skill URL or download the bundle. The skill describes when to use the decision, the inputs it requires, its scope, and how to invoke it. 06 What does Decision Control Tower add? Tower adds OIDC-backed role-based access, custom promotion workflows, accountable human tasks, explicit environment promotion, and traceable release records. Decision Control is the analyst workspace; Tower is the enterprise operating layer around it. 07 Can I import my existing DMN files? Yes. Open an existing DMN model in Decision Control and continue authoring, evaluating, testing, and publishing it from the visual workspace. 08 How is Decision Control different from Business Central? Business Central is a broader, developer-oriented authoring environment. Decision Control focuses on the governed DMN lifecycle for policy owners and analysts: visual authoring, live value inspection, reviewable AI changes, reusable scenario tests, publish verification, agent skills, and execution evidence. It is not positioned as a drop-in replacement for every Business Central capability. Ready to Prove It on a Real Policy? ## Take One Decision From Policy to Production Bring an existing DMN model or start from a policy. See how Decision Control helps your team model, test, review, publish, and trace it in one governed lifecycle. [See Decision Control in Action](https://aletyx.ai/free-trial/) [Talk to Our Team](https://aletyx.ai/contact/) No Java required. Use your own model or start with a guided example. --- # Govern your enterprise decisions with accountable AI Source: https://aletyx.ai/decision-intelligence/ Decision Intelligence Aletyx combines generative AI with deterministic business policies and visual decision models to deliver automated decisions that you can trace and defend in an audit. [Try a guided pilot](https://aletyx.ai/free-trial/) Watch a 2-minute overview No rewrite required Backward compatibility Flat-fee pricing ## You cannot automate regulated business functions with probabilistic AI You‘re under pressure to automate pricing, risk and eligibility. But without deterministic policy controls, AI models can drift and generate variances that you cannot explain or defend in an audit ### You can’t trust GenAI alone LLMs are reasoning engines, not knowledge bases. You cannot safely deploy AI in regulated environments without strict deterministic rules. ### 99% accuracy = 100% failure Generative models fluctuate by design. Variance is a strict compliance violation when processing mission-critical business decisions. ### AI decisions are hard to defend Decisions must be proved in audits. AI-driven outcomes are indefensible in production unless you have immutable execution lineage. Why Aletyx ## Aletyx keeps your policies current, provable and under control AI finds patterns, but your policies control them. Aletyx embeds AI safely inside your deterministic rule boundary. Your outcomes will remain governed, defensible, and strictly based on proof — not probabilities. [Try a guided pilot](https://aletyx.ai/free-trial/) You run Drools or an existing rules platform ### Modernize Drools, RHDM, and BRMS without a rewrite Aletyx provides a fully compatible execution engine that moves your legacy workloads to a modern, governed stack without starting from scratch. AI influences pricing, eligibility, or risk ### Control AI when it touches money or compliance You need a clear rule boundary whenever AI affects customer outcomes or regulatory exposure. Aletyx acts as a deterministic guardrail by design. Regulators or auditors require proof ### Provide evidence, not explanations Aletyx captures complete execution lineage and gives you versioned, repeatable decisions that you can replay and prove to auditors. Governance must exist before production ### Enforce approvals before you are exposed Governance must happen before deployment. Aletyx enforces approvals in your delivery flow — so only vetted decision changes reach production. One platform. Three layers of control. ## Unify your enterprise decisions with one operating model Aletyx is a unified platform for compliance-heavy sectors and mission-critical operations. Three integrated layers offer a consistent way to define decisions, run them reliably and ensure secure end-to-end governance. Infrastructure Infrastructure ### For existing workloads: Modernize your Drools workloads and prepare for AI, without rewrites Aletyx Enterprise Build of Drools modernizes your rules engine without rewrites — a modern, secure and AI-capable foundation that preserves the behavior of your existing rules. - **Preserve existing behavior:** Migrate BAMOE v8, RHDM, and Red Hat BRMS workloads with full v7/v8 compatibility and exact execution semantics. - **Upgrade to a modern stack:** Eliminate legacy dependencies and move workloads safely to Spring Boot, Kubernetes, and cloud-native environments. - **Enable native AI capabilities:** Use MCP integration so your existing rules become safe, deterministic guardrails for generative AI. - **Secure enterprise operations:** Get active CVE patches, compatibility testing, and long-term support without forced, costly rewrites. [Explore Enterprise Drools](https://aletyx.ai/enterprise-drools/) ![Drools logo](https://aletyx.ai/_astro/drools-logo.BNHe_eeB_1b9VsG.webp) Experience & Runtime Experience & Runtime ### For business-wide initiatives: Model and automate deterministic AI decisions at scale Aletyx Decision Control gives business analysts autonomy to design, test and publish rules without engineering bottlenecks in an intuitive interface. - **Give your analysts autonomy:** Policy owners gain ownership to model, test, publish decisions and manage complex rules without IT bottlenecks - **Embed AI at the model level:** MCP integration allows AI agents to safely discover, understand, and execute decisions directly from your catalog. - **Combine rules and human judgment:** Blend deterministic rules, AI recommendations and human escalations into one auditable workflow. - **Maintain architectural control:** Architects own the integrations and infrastructure, while business analysts safely own the decision policy. [Explore Decision Control](https://aletyx.ai/decision-control/) Governance Governance ### For compliance: Prevent compliance failures before they reach production Aletyx Decision Control Tower governs environment promotion with role-based access control, custom workflows, accountable tasks, and traceable release records. - **Enforce pre-production checks:** Decision changes only ship to production after successfully passing your organization's strict validation gates. - **Maintain complete traceability:** Reproduce any decision with its exact inputs and policy version to satisfy regulatory audits. - **Fit your existing delivery pipelines:** Plug customizable approval workflows directly into your CI/CD processes for role-based promotion. - **Secure enterprise access:** Automate governance without changing your stack using industry-standard OpenID Connect and corporate integrations. [Explore Decision Control Tower](https://aletyx.ai/decision-control-tower/) ## AI proposes insights.Policies guarantee outcome. You’re under pressure to bring AI into pricing, risk and eligibility. LLMs can speed up outcomes. But without deterministic policy controls, you will generate variances that you cannot explain or defend. ### Risk compliance failures without Aletyx **Your AI models drift without control.** Models change and your outcomes drift. You’d struggle to explain and defend these decisions to an auditor. ### Modernize and govern with Aletyx **Your policies act as deterministic guardrails.** AI insights are treated as inputs and verified against policies before they become production outcomes. ### Example: **Approve a complex pricing discount** **An LLM analyzes the customer context and suggests a 15 percent discount.** The decision engine executes deterministically to enforce margin floors, eligibility and compliance. It blocks unsafe outcomes before they ever hit your ledger. You don’t need to govern every AI interaction. You need to govern revenue, risk, and compliance decisions. [Try a guided pilot](https://aletyx.ai/free-trial/) ## Built for the Architect. Designed for the Audit. Modernize without a rewrite. Add AI without loss of control. Prove the result when it matters. ### For the Platform Architect - Run on any cloud: Deploy across Kubernetes distributions and container orchestration platforms. - Scale your decisions: Operate statelessly to handle high-throughput enterprise decisioning. - Integrate without lock-in: Fit into your CI/CD pipelines without proprietary deployment constraints. - Build on open standards: Leverage proven DMN, Drools, and Model Context Protocol (MCP). ### For the Executive Sponsor - Stand behind every decision: Maintain a complete, replayable history for every execution. - Deliver policy changes faster: Update business rules safely without requiring full application releases. - Adopt AI without risk: Introduce intelligence without non-deterministic threats to core systems. - Eliminate pricing surprises: Secure predictable, flat-fee pricing without per-decision or per-core penalties. A Clear Choice for Enterprises ## Only Aletyx can deliver zero rewrites, native AI and flat pricing. Consideration Aletyx IBM (BAMOE) Red Hat Apache KIE Server support Fully restored and modernized - v8 fast approaching EOL - removed in v9 End of life - Not transferred - to Apache Modernization approach No-rewrite for existing, cloud-native for new - v8 fast approaching EOL - v9 requires full rewrite N/A Kogito only — no backward continuity AI capabilities Native on both runtimes: MCP, AI nodes, LLM Bolt-on None None Enterprise scaling Scalable Process (Kogito exclusive) Limited None Not available Security Active CVE patching on both runtimes v8 fast approaching EOL End of life No SLA, no patches Support Direct access to core engineers Tiered L1→L3 Unavailable Volunteer-based, no SLA Pricing Flat fee, predictable Per-core, yearly increases N/A Free (high internal cost) Consideration ### KIE Server support Aletyx Fully restored and modernized IBM (BAMOE) - v8 fast approaching EOL - removed in v9 Red Hat End of life Apache - Not transferred - to Apache Consideration ### Modernization approach Aletyx No-rewrite for existing, cloud-native for new IBM (BAMOE) - v8 fast approaching EOL - v9 requires full rewrite Red Hat N/A Apache Kogito only — no backward continuity Consideration ### AI capabilities Aletyx Native on both runtimes: MCP, AI nodes, LLM IBM (BAMOE) Bolt-on Red Hat None Apache None Consideration ### Enterprise scaling Aletyx Scalable Process (Kogito exclusive) IBM (BAMOE) Limited Red Hat None Apache Not available Consideration ### Security Aletyx Active CVE patching on both runtimes IBM (BAMOE) v8 fast approaching EOL Red Hat End of life Apache No SLA, no patches Consideration ### Support Aletyx Direct access to core engineers IBM (BAMOE) Tiered L1→L3 Red Hat Unavailable Apache Volunteer-based, no SLA Consideration ### Pricing Aletyx Flat fee, predictable IBM (BAMOE) Per-core, yearly increases Red Hat N/A Apache Free (high internal cost) Your last chance ## Try a free guided pilot and explore safe generative AI Let's talk about how Aletyx can modernize your Drools, RHDM, and BRMS workloads. Our architects are ready to help you. [Try a guided pilot](https://aletyx.ai/free-trial/) --- # The Enterprise Drools Engine. Modern, Hardened, AI-Ready. Source: https://aletyx.ai/enterprise-drools/ Built by original team members of Drools. Trusted in mission-critical systems worldwide. Modernize Drools, RHDM, and BRMS workloads with restored backward compatibility, active CVE patching, and native AI via MCP. Your rules stay. The risk doesn’t. [Assess My Migration Path](https://aletyx.ai/contact/) [Talk to an Aletyx Architect](https://aletyx.ai/contact/) If it runs on Drools, RHDM, or BRMS, it runs on Aletyx. Based on Apache Drools 10.x with full backward compatibility restored. No rewrite required Backward compatibility Flat-fee pricing ## Your Drools Runtime Is Aging. The Risks Are Not. Community releases are years out of date. IBM BAMOE v8 is approaching end of life. Red Hat exited entirely. And community Drools 10.x introduces breaking changes — a direct upgrade from v7 or v8 will break your existing logic. You cannot afford to stay. You also cannot afford a rewrite. Aletyx gives you a third path. [See how Aletyx preserves your existing workloads](https://aletyx.ai/modernization/) ## The Drools Engine You Trust Hardened for What Comes Next Everything in Apache Drools 10.x, plus what should have been there all along: restored backward compatibility, enterprise hardening, predictable support, and native AI capabilities. Built and maintained by original team members that led Drools at Red Hat and IBM. You replace your runtime. Your rules, orchestration, and behavior stay the same. [Start a guided evaluation](https://aletyx.ai/contact/) ## What the Enterprise Build Delivers [Assess My Migration Path](https://aletyx.ai/contact/) ### Zero-Rewrite Compatibility Full support for existing DRL, DMN, Excel decision tables, and BPMN-based rule orchestration, including restored startProcess(). Your regression tests pass. Your logic stays identical. ### Enterprise Hardening Active CVE monitoring and patching. Signed builds. Controlled dependency baselines. Predictable release cycles, no forced upgrades, no breaking changes. ### Up to 30× Faster Orchestration BPMN-based rules orchestration runs up to 30× faster than community Drools 10.x, without touching your code. ### Native AI via MCP First Drools engine with native Model Context Protocol support. LLMs discover, query, and execute your decisions within governed boundaries. Every interaction is validated and logged. ### Modern Runtime Java 17+ (path to 21). Spring Boot 3 and Quarkus. Kubernetes-ready. Standard CI/CD no proprietary lock-in. ## The Aletyx Platform Scenario Why Aletyx You run Drools, RHDM, or BRMS in production Runtime swap with validation. No rewrite project. You use BPMN-based rules orchestration Community Drools 10 broke it. Aletyx restored and optimized it. You face audit or compliance requirements Versioned, deterministic, reproducible decisions you can prove. You are evaluating AI for core decisions Native MCP lets AI assist while your rules enforce boundaries. Scenario You run Drools, RHDM, or BRMS in production Why Aletyx Runtime swap with validation. No rewrite project. Scenario You use BPMN-based rules orchestration Why Aletyx Community Drools 10 broke it. Aletyx restored and optimized it. Scenario You face audit or compliance requirements Why Aletyx Versioned, deterministic, reproducible decisions you can prove. Scenario You are evaluating AI for core decisions Why Aletyx Native MCP lets AI assist while your rules enforce boundaries. ## The Upgrade Path Others Offer Isn’t an Upgrade Consideration Aletyx IBM BAMOE Community Drools 10 Backward compatibility Full v7/v8 continuity Breaking changes v8→v9 Breaking changes from v7/v8 BPMN orchestration Restored and optimized Removed in v9 Removed Security Active CVE patching v8 EOL; v9 quarterly No SLA, no patches AI integration Native MCP Limited, IBM-aligned None Support Direct access to core engineers Tiered L1→L3 Community forums Pricing Flat fee, predictable Per-core, yearly increases Free (high internal cost) Consideration ### Backward compatibility Aletyx Full v7/v8 continuity IBM BAMOE Breaking changes v8→v9 Community Drools 10 Breaking changes from v7/v8 Consideration ### BPMN orchestration Aletyx Restored and optimized IBM BAMOE Removed in v9 Community Drools 10 Removed Consideration ### Security Aletyx Active CVE patching IBM BAMOE v8 EOL; v9 quarterly Community Drools 10 No SLA, no patches Consideration ### AI integration Aletyx Native MCP IBM BAMOE Limited, IBM-aligned Community Drools 10 None Consideration ### Support Aletyx Direct access to core engineers IBM BAMOE Tiered L1→L3 Community Drools 10 Community forums Consideration ### Pricing Aletyx Flat fee, predictable IBM BAMOE Per-core, yearly increases Community Drools 10 Free (high internal cost) [Get a detailed migration assessment](https://aletyx.ai/contact/) ## Zero-Rewrite Migration in Three Steps Most teams see their first successful execution in under 15 minutes. ### Diagnose Our tools analyze your repositories to map dependencies and versions. No code changes. ### Swap Replace your Drools runtime with the Enterprise Build. Your rule assets stay untouched. ### Validate Run your existing tests. Confirm identical logic with improved performance and security. [Request a Free Migration Assessment](https://aletyx.ai/contact/) [Talk to an Aletyx Architect](https://aletyx.ai/contact/) Frequently Asked Questions ## Clear answers to your questions. [Get my assessment report](https://aletyx.ai/contact/) 01 Is Aletyx compatible with my existing Drools, RHDM, or BRMS projects? Yes. Backward compatibility with v7 and v8 is restored. Your DRL, DMN, Excel decision tables, and BPMN-based rule orchestration carry forward to the Enterprise Build with no rewrite. Your regression tests pass. Your behavior stays identical. 02 What about startProcess and BPMN rules orchestration? Fully restored. Community Drools 10.x removed startProcess and BPMN-based rule flows. The Enterprise Build brings them back, validated end to end, with performance improvements on top. 03 Does it include everything in Apache Drools 10.x? Yes, and more. The Enterprise Build is a superset. Everything in Apache Drools 10.x, plus restored v7/v8 compatibility, enterprise hardening, native AI via MCP, and predictable release management. 04 What support do I get? Engineer-led support with direct access to the team behind the product. No tiered L1 to L3 bouncing. SLA and coverage scale with your subscription tier — see the pricing page for details. 05 How long does migration typically take? It varies with application size, but an average application can be migrated in about a week. Because backward compatibility is restored, most of the effort goes into validation rather than rewriting your rules. Start with a free 60-day evaluation and we’ll help scope yours in the first call. Your last chance ## Modernize Your Drools Runtime.Keep Your Rules. Add AI. The exact code running today will run on Aletyx tomorrow — faster, safer, and AI-ready. [Start My Free 60-Day Evaluation](https://aletyx.ai/free-trial/) [Talk to an Aletyx Architect](https://aletyx.ai/contact/) (No credit card required. Full engine access. Direct engineering support.) --- # Your KIE Server. Modernized. AI-Ready. No Rewrite. Source: https://aletyx.ai/enterprise-kie-server/ Built by original team members of jBPM and KIE Server. Enterprise workflow continuity for the AI era. Aletyx Enterprise Build of KIE Server is a drop-in replacement for your existing RHPAM, BAMOE v8, jBPM, and KIE Server workloads running on Java 21, Jakarta EE 10, Spring Boot 3, and a modern application server. With native AI capabilities. Without touching your code. [Assess My Migration Path](https://aletyx.ai/free-trial/) [Talk to an Aletyx Architect](https://aletyx.ai/contact/) If it runs on KIE Server, it runs on Aletyx. Same APIs. Same behavior. Modern stack. Native AI. Zero rewrites Drop-in modernization Flat-fee pricing ## The Vast Majority of Production Workflows Run on KIE Server. The Community Moved On. KIE Server was never transferred to Apache. There are no more open-source releases. The last community version is nearly three years old — riddled with unpatched vulnerabilities. IBM BAMOE v8 is end of life. v9 removes KIE Server entirely. Red Hat PAM is end of life. The community's answer — Kogito — is a fundamentally different architecture that requires a complete rewrite of every workflow asset. For the vast majority of production KIE workflow workloads running on KIE Server today, there is no upgrade path. Only a rewrite — or Aletyx. [See the difference in action](https://aletyx.ai/contact/) ## Moving to Kogito Is Not a Migration. It's a Rewrite. KIE Server and Kogito are architecturally different systems. Different execution models. Different persistence. Different deployment. Different APIs. Every BPMN asset, every integration, every human task configuration must be revisited. This is not a version upgrade — it's a multi-quarter, multi-team program with high delivery risk. For enterprises running hundreds of process definitions across critical systems, the cost and risk are prohibitive. Aletyx understands that you cannot rewrite your core business systems because a new version exists. Continuity is not optional — it's the requirement. [Explore the drop-in alternative](https://aletyx.ai/contact/) ## KIE Server — Restored, Modernized, AI-Ready Aletyx brought KIE Server back. We modernized the runtime from the ground up — modern JVM, modern frameworks, modern application server — while preserving complete behavioral compatibility with your existing workloads. Built and maintained by original team members that led jBPM and KIE Server at Red Hat. Your processes, your integrations, your behavior — unchanged. Your stack — modern, secure, and AI-ready. [Start a guided evaluation](https://aletyx.ai/free-trial/) ## What the Enterprise Build Delivers [Assess My Migration Path](https://aletyx.ai/free-trial/) ### Drop-In Replacement Same APIs. Same execution semantics. Same process behavior. Deploy your existing KJARs on a modern, secure runtime. Your regression tests pass. Your integrations stay intact. ### Modern Stack Java 21. Jakarta EE 10. Spring Boot 3. EAP 8.x. No more legacy application servers, no more outdated dependencies. A production runtime built for today's enterprise infrastructure. ### Native AI Capabilities The same AI capabilities available in Aletyx Enterprise Build of Kogito — now in KIE Server. MCP-based process triggering. AI Agent node. Direct LLM invocation. Modernize with AI without rewriting a single workflow. ### Active Security CVE monitoring and patching on a predictable cadence. The last community release carries years of unpatched vulnerabilities. Aletyx eliminates that exposure. ### Enterprise Hardening Active CVE monitoring and patching. Signed builds. Controlled dependency baselines. Predictable release cycles, no forced upgrades, no breaking changes. ## Bring AI to Your KIE Server. No Rewrite Required. The industry assumption is that AI requires a platform rewrite. Aletyx rejects that premise. We are bringing the full AI capability stack — the same capabilities shipping in Aletyx Enterprise Build of Kogito directly to KIE Server ### MCP Process Triggering AI agents discover and trigger your existing processes via Model Context Protocol. ### AI Agent Node Embed intelligent, ad-hoc AI tasks inside your existing BPMN workflows. ### Direct LLM Invocation Call language models as native workflow steps — no external integration layer. Your existing workflows gain AI capabilities. Your architecture stays the same. Your behavior stays deterministic. [See AI on KIE Server in action](https://aletyx.ai/contact/) ## When the Enterprise Build Is the Right Choice Scenario Why Aletyx You run RHPAM, BAMOE v8, jBPM, or KIE Server in production Drop-in replacement. Modern stack. No rewrite. You've been told to "migrate to Kogito" That's a rewrite. Aletyx gives you modernization without architectural change. You need AI in your existing workflows Native AI capabilities — same as Kogito — delivered on KIE Server. You face unpatched CVEs on aging runtimes Active security patching. Modern dependencies. Enterprise SLAs. Your vendor's support has become an empty policy Direct access to the engineers who built KIE Server. Scenario You run RHPAM, BAMOE v8, jBPM, or KIE Server in production Why Aletyx Drop-in replacement. Modern stack. No rewrite. Scenario You've been told to "migrate to Kogito" Why Aletyx That's a rewrite. Aletyx gives you modernization without architectural change. Scenario You need AI in your existing workflows Why Aletyx Native AI capabilities — same as Kogito — delivered on KIE Server. Scenario You face unpatched CVEs on aging runtimes Why Aletyx Active security patching. Modern dependencies. Enterprise SLAs. Scenario Your vendor's support has become an empty policy Why Aletyx Direct access to the engineers who built KIE Server. ## No One Else Offers KIE Server Continuity Consideration Aletyx IBM (BAMOE) Red Hat (PAM) Apache Community KIE Server support Fully restored and modernized EOL in v8, removed in v9 End of life Not transferred to Apache Migration approach Drop-in replacement Rewrite to v9 N/A Rewrite to Kogito Runtime stack Java 21, Jakarta EE 10, Spring Boot 3, EAP 8.x Frozen at outdated stack Frozen No releases AI capabilities Native: MCP, AI Agent node, LLM invocation None on KIE Server None None Security Active CVE patching v8 EOL priority End of life No SLA, no patches Support Direct access to core engineers Tiered L1→L3 Unavailable Volunteer-based, no SLA Pricing Flat fee, predictable Per-core, yearly increases N/A Free (high internal cost) Consideration ### KIE Server support Aletyx Fully restored and modernized IBM (BAMOE) EOL in v8, removed in v9 Red Hat (PAM) End of life Apache Community Not transferred to Apache Consideration ### Migration approach Aletyx Drop-in replacement IBM (BAMOE) Rewrite to v9 Red Hat (PAM) N/A Apache Community Rewrite to Kogito Consideration ### Runtime stack Aletyx Java 21, Jakarta EE 10, Spring Boot 3, EAP 8.x IBM (BAMOE) Frozen at outdated stack Red Hat (PAM) Frozen Apache Community No releases Consideration ### AI capabilities Aletyx Native: MCP, AI Agent node, LLM invocation IBM (BAMOE) None on KIE Server Red Hat (PAM) None Apache Community None Consideration ### Security Aletyx Active CVE patching IBM (BAMOE) v8 EOL priority Red Hat (PAM) End of life Apache Community No SLA, no patches Consideration ### Support Aletyx Direct access to core engineers IBM (BAMOE) Tiered L1→L3 Red Hat (PAM) Unavailable Apache Community Volunteer-based, no SLA Consideration ### Pricing Aletyx Flat fee, predictable IBM (BAMOE) Per-core, yearly increases Red Hat (PAM) N/A Apache Community Free (high internal cost) [Get a detailed migration assessment](https://aletyx.ai/contact/) ## If It Works, Modernize It. Don't Rewrite It. If your KIE Server workloads run well today, you do not need to move to Kogito. Aletyx Enterprise Build of KIE Server gives you a modern, secure, AI-ready runtime — and that is a complete, long-term answer. Aletyx Enterprise Build of Kogito is the right choice for greenfield projects — new workflows built cloud-native from the start. Unless you have a specific business demand that requires rearchitecting your current systems, there is no reason to rewrite what already works. Modernize what you have. Build new on Kogito. Never be forced into a rewrite you don't need [See how Aletyx preserves your existing workloads](https://aletyx.ai/contact/) Frequently Asked Questions ## Clear answers to your questions. [Talk to our team](https://aletyx.ai/contact/) 01 Is this a drop-in replacement for my existing RHPAM, BAMOE v8, jBPM v7, or KIE Server deployment? Yes. Same APIs. Same execution semantics. Same process behavior. Your existing KJARs deploy directly onto the Enterprise Build. Your regression tests pass. Your integrations stay intact. 02 What stack does it run on? Java 21. Jakarta EE 10. Spring Boot 3. EAP 8.x and WildFly 35+. Kubernetes-ready. No more legacy application servers or outdated dependencies. 03 Why not just migrate to Kogito? Moving to Kogito is a rewrite, not a migration. Kogito and KIE Server are architecturally different, different execution model, different persistence, different deployment, different APIs. Every BPMN asset and every integration has to be revisited. For workloads that already run well, that is a multi-quarter program with no new business value. Aletyx gives you a modern, AI-ready runtime without the rewrite. 04 What happened to KIE Server in the open-source ecosystem? KIE Server was never transferred to Apache. The last community release is nearly three years old. The community focused on Kogito instead, which is a different architecture. Aletyx restored KIE Server as a fully supported, modernized product. 05 What AI capabilities are available? The same AI capabilities shipping in Aletyx Enterprise Build of Kogito. MCP-based process triggering so AI agents can discover and invoke your workflows. AI Agent nodes for intelligent steps inside BPMN. Direct LLM invocation as a native workflow task. All governed by the deterministic engine around them. 06 Can I use Business Central with this? Yes. We work with existing Business Central deployments for customers who rely on it today, and we collaborate with the customer on moving to an updated authoring and monitoring toolset over time. Decision Control is not a Business Central replacement — it is a different approach that delivers some of the same benefits with a different model. 07 What support do I get? Engineer-led support with direct access to the team behind the product. No tiered L1 to L3 bouncing. SLA and coverage scale with your subscription tier — see the pricing page for details. 08 How long does migration typically take? It varies with application size, but an average application can be migrated in about a week. Since the runtime is a drop-in replacement, most of the effort is validation rather than code changes. We can scope yours during a free 60-day evaluation. Your last chance ## Modernize KIE Server.Add AI. No Rewrite. The exact processes running today will run on Aletyx tomorrow on a modern stack, with native AI, and full enterprise support. [Start My Free 60-Day Evaluation](https://aletyx.ai/free-trial/) [Talk to an Aletyx Architect](https://aletyx.ai/contact/) No credit card. Full access. Direct support. --- # AI-Native Workflows. Deterministic Where It Matters. Source: https://aletyx.ai/enterprise-kogito/ Built by original team members of jBPM and Kogito. Deterministic workflows for the AI era. Aletyx Enterprise Build of Kogito brings AI deep into your workflows — while guaranteeing that core system operations stay deterministic, auditable, and governed. The engine for enterprises that need both intelligence and certainty. [Start a Guided Evaluation](https://aletyx.ai/free-trial/) [Talk to Our Team](https://aletyx.ai/contact/) AI agents coordinate. Your workflows execute. Enterprise-exclusive Scalable Process. Native AI integration. Deterministic behavior at the engine level. Scalability AI Ready Flat-fee pricing ## Not All Workflows Are the Same AI workflow tools automate interactions between systems — connecting APIs, routing data, orchestrating agents. That's valuable for integration. But when a workflow is the system operation — payment processing, claims adjudication, loan origination — you need deterministic execution. The outcome must be guaranteed, recorded, and reproducible. AI can inform the process. It cannot run the process. Aletyx Enterprise Build of Kogito is built for the second category: workflows where the behavior is the business logic, not just the glue between services. **AI agents decide how to interact. Your workflows decide how to execute.** [See the difference in action](https://aletyx.ai/contact/) ## AI-Native. Deterministic at the Core. Everything in the community edition, plus what enterprises actually need: Scalable Process for horizontal execution, native AI capabilities at the engine level, and the deterministic guarantees that regulated industries require. Built and maintained by original team members that led jBPM and Kogito. AI participates in your workflows. Your workflows guarantee the outcome. [Explore the architecture](https://aletyx.ai/contact/) ## What the Enterprise Build Delivers [Start a Guided Evaluation](https://aletyx.ai/free-trial/) ### Native AI Integration AI agents trigger processes via MCP. AI Agent nodes handle ad-hoc intelligent tasks inside workflows. Direct LLM invocation nodes call language models as workflow steps. AI is embedded at the engine level — not bolted on. ### Deterministic Execution When AI informs a decision and the workflow acts on it, execution is deterministic. Every step is guaranteed, recorded, and reproducible. No probabilistic drift in core system operations. ### Scalable Process (Enterprise Exclusive) Distributes workflow state, execution, and persistence across your infrastructure. Horizontal scaling. Not available in the community edition. ### Scalable Job Service Multi-node job scheduling without leader election. Reliable timer and deadline execution across distributed environments — no single point of failure. ### Human Task Integration Full context preservation across human interactions. Coordinate complex operations across teams, systems, and approval chains — with complete state continuity. ### Enterprise Hardening Active CVE monitoring and patching. Signed builds. Controlled dependency baselines. Predictable release cycles, no forced upgrades, no breaking changes. ## Let AI Coordinate. Let Workflows Execute. Agentic AI is transforming how systems interact. AI agents route, recommend, and orchestrate across tools and services. That layer is dynamic, adaptive, and probabilistic — by design. But when an agent triggers a core business operation — process a payment, adjudicate a claim, execute a trade — the execution must be deterministic. The bill gets paid. The claim gets recorded. The outcome is provable. Aletyx Enterprise Build of Kogito sits at this boundary. AI agents connect to your workflows via MCP. The agent decides when and what. The workflow guarantees how. [See It in Action](https://aletyx.ai/contact/) ## Decisions and Workflows — One Platform Aletyx Enterprise Build of Kogito integrates seamlessly with Aletyx Enterprise Build of Drools and Decision Control. Deterministic rules govern the "what." Workflows orchestrate the "how." AI assists within boundaries you define. Decisions, workflows, and AI — under control. [See It in Action](https://aletyx.ai/contact/) ## When the Enterprise Build Is the Right Choice Scenario Why Aletyx AI agents trigger core business operations AI-native. Agents coordinate. Workflows guarantee execution. You need deterministic behavior in regulated environments Every step recorded, reproducible, and auditable. You need workflows at scale Out of the box horizontal scale — enterprise exclusive. Scenario AI agents trigger core business operations Why Aletyx AI-native. Agents coordinate. Workflows guarantee execution. Scenario You need deterministic behavior in regulated environments Why Aletyx Every step recorded, reproducible, and auditable. Scenario You need workflows at scale Why Aletyx Out of the box horizontal scale — enterprise exclusive. ## Different Tools for Different Problems Consideration Aletyx Enterprise Build of Kogito AI Workflow Tools (n8n, etc.) Community Edition Primary purpose Defines how the application itself works Integration among systems and services Defines how the application itself works (limited scale) AI integration Engine-level: MCP, AI nodes, LLM invocation AI-first orchestration None Execution guarantee Deterministic, reproducible Dynamic, adaptive Deterministic Scalable Process Enterprise exclusive N/A Not available Regulated industries Built for audit and compliance Focused on integration scenarios Basic Support Direct access to core engineers Community / SaaS Community forums Pricing Flat fee, predictable Usage-based Free (high internal cost) Consideration ### Primary purpose Aletyx Enterprise Build of Kogito Defines how the application itself works AI Workflow Tools (n8n, etc.) Integration among systems and services Community Edition Defines how the application itself works (limited scale) Consideration ### AI integration Aletyx Enterprise Build of Kogito Engine-level: MCP, AI nodes, LLM invocation AI Workflow Tools (n8n, etc.) AI-first orchestration Community Edition None Consideration ### Execution guarantee Aletyx Enterprise Build of Kogito Deterministic, reproducible AI Workflow Tools (n8n, etc.) Dynamic, adaptive Community Edition Deterministic Consideration ### Scalable Process Aletyx Enterprise Build of Kogito Enterprise exclusive AI Workflow Tools (n8n, etc.) N/A Community Edition Not available Consideration ### Regulated industries Aletyx Enterprise Build of Kogito Built for audit and compliance AI Workflow Tools (n8n, etc.) Focused on integration scenarios Community Edition Basic Consideration ### Support Aletyx Enterprise Build of Kogito Direct access to core engineers AI Workflow Tools (n8n, etc.) Community / SaaS Community Edition Community forums Consideration ### Pricing Aletyx Enterprise Build of Kogito Flat fee, predictable AI Workflow Tools (n8n, etc.) Usage-based Community Edition Free (high internal cost) [Get a detailed architecture review](https://aletyx.ai/contact/) ## Full Visibility Into Every Workflow Execution logs, audit trails, state transitions, and performance metrics — across every instance. Prometheus-native. Built for regulated and mission-critical environments. ![Aletyx Enterprise workflow monitoring dashboard](https://aletyx.ai/_astro/Dark%20Mode%20Screen%20Recreation.D0tcFtk6_Z2lAt6q.webp) Frequently Asked Questions ## Clear answers to your questions. [Get my assessment report](https://aletyx.ai/contact/) 01 How is Aletyx Enterprise Build of Kogito different from AI workflow tools like n8n? n8n and similar tools are built for integration among systems and services, connecting APIs, routing data, orchestrating agents. Kogito defines how the application itself works, with deterministic execution, full audit, and enterprise scale. You use n8n to glue services together. You use Kogito when the workflow is the business logic. 02 Is this a replacement for jBPM v7? No. For teams running jBPM v7, KIE Server, RHPAM, or BAMOE v8 in production, the right product is Aletyx Enterprise Build of KIE Server, which is a drop-in replacement. Enterprise Build of Kogito is built for greenfield projects, new workflows, cloud-native from the start. 03 What is Scalable Process? An enterprise-exclusive capability that distributes workflow state, execution, and persistence across your infrastructure for horizontal scaling. Not available in the community edition. Built for high-throughput, stateful processes where a single-node engine is not enough. 04 What AI capabilities are included? MCP integration so AI agents trigger and interact with your workflows. AI Agent nodes for intelligent tasks inside the process. Direct LLM invocation as a native workflow step. All deterministic at the engine level, with full audit of every interaction. 05 Does Aletyx Enterprise Build of Kogito work with Aletyx Enterprise Build of Drools? Yes. They are complementary. Drools governs the "what", the deterministic rules that define your policies. Kogito orchestrates the "how", the workflow that carries them out. Together with Decision Control, they form one coherent platform. 06 What support do I get? Engineer-led support with direct access to the team behind the product. No tiered L1 to L3 bouncing. SLA and coverage scale with your subscription tier — see the pricing page for details. Your last chance ## AI-Native Workflows.Deterministic Execution.Every Step Proven. Let AI coordinate. Let your workflows guarantee the outcome. [Start My Free 60-Day Evaluation](https://aletyx.ai/free-trial/) [Talk to Our Team](https://aletyx.ai/contact/) No credit card. Full access. Direct support. --- # Aletyx at AI_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN Source: https://aletyx.ai/events/aletyx-at-ai_dev-2025/ [Events & Community](https://aletyx.ai/topics/events-and-community/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [DMN](https://aletyx.ai/topics/dmn/) September 19, 2025 2 min ![Warm orange and blue lights in a conference venue](https://aletyx.ai/_astro/event-hero.BKDNyS92_2jk063.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) and [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Published September 19, 2025 At [AI\_dev Europe](https://events.linuxfoundation.org/ai-dev-europe/) in Amsterdam, Aletyx addressed one of the toughest challenges in enterprise AI adoption: how to go beyond hype demos and MVPs and create intelligent solutions that can be trusted in production. This challenge is bigger than technology alone: [according to Forbes](https://www.forbes.com/sites/andreahill/2025/08/21/why-95-of-ai-pilots-fail-and-what-business-leaders-should-do-instead/), 95% of enterprise AI pilots **fail** not because of technology but because of weak strategy, culture, and integration. This is why enterprises must rethink their approach and strengthen their architectural foundations. If most enterprises fail in their AI journey, the real question is “*how to be among the few that succeed*?”. And **this** is exactly what our session at AI\_dev Europe was about. > [Architecting the AI Bridge: Integrating LLMs and DMN With Drools, Spring Boot, and the MCP Protocol](https://aideveu2025.sched.com/event/25Tv5/architecting-the-ai-bridge-integrating-llms-and-dmn-with-drools-spring-boot-and-the-mcp-protocol-tim-wuthenow-alex-porcelli-aletyx-inc) > > 📅 Friday, Aug 29, 2025 – 1:35 PM CEST > 📍 AI\_dev Venue, Rooms G001 & G002 > 🎙️ Tim Wuthenow & Alex Porcelli, Aletyx Co-founders > > *Couldn’t make it to our talk at AI\_dev Europe?* **Recorded session is available *here*!** [Video: YouTube video player](https://www.youtube.com/embed/-hemGXHpKh0?si=WWNhWTgsnYE__xo_) ### Session Recap: Aletyx at AI\_dev Europe 2025 In this session, [Tim Wuthenow](https://www.linkedin.com/in/timwuthenow/?utm_medium=event&utm_campaign=event&utm_source=blog&utm_content=aidev) and [Alex Porcelli](https://www.linkedin.com/in/alexporcelli/) addressed a critical enterprise challenge when pushing AI innovation in core systems: the fact that GenAI is statistically correct, *but situationally wrong*. And the risks associated with the lack of accuracy within high-stakes scenarios. We covered a hybrid AI architecture that pairs the conversational power of LLMs with the auditable, deterministic logic of DMN and Drools. The talk demonstrated how this approach allows us to update the AI’s reasoning **in real-time**, creating an intelligent system that is not only compliant but also instantly adaptable to changing business policies, making it safe for core enterprise use. ### A Quick Glimpse: Conference Snapshots 📸 We all know that tech conferences are more than sessions… It’s always a great opportunity to build new connections and have a great time with old friends. *Thanks to everyone who attended our session or watched the replay online!* If you have any questions or points you’d like to discuss further, don’t hesitate to [reach out](https://aletyx.ai/contact/)! ![AI\_dev Europe 2025 conference snapshots](https://aletyx.ai/_astro/ai_dev2025-slicer.sq0GWYgQ_j68Fa.webp) ![Aletyx presenting Decision Intelligence at AI\_dev Europe 2025](https://aletyx.ai/_astro/ai_dev2025-alex-tim.JkOhWNf9_1yFSRJ.webp) ![Tim shows GenAI following Drools guardrails](https://aletyx.ai/_astro/ai_dev2025-tim.C_y-lzHN_1JnyLD.webp) ![Alex demonstrates how to architect enterprise AI with Drools, GenAI and DMN](https://aletyx.ai/_astro/ai_dev2025-alex.CdymCCm4_2pACyu.webp) We can help move AI out of the sandbox and into production with confidence. 🔗 [Get in touch](https://aletyx.ai/contact/) stay connected at [LinkedIn](https://www.linkedin.com/company/aletyx?utm_source=aletyx.ai). --- *Aletyx builds enterprise-grade Drools, Kogito, and DMN solutions backed by built-in AI. Let’s talk about how your enterprise can scale GenAI with confidence.* ## References 1. [AI\_dev Europe](https://events.linuxfoundation.org/ai-dev-europe/) — Linux Foundation Events ## About the authors [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Co-founder & CCO More than 15 years putting rules, process, and AI to work where enterprise decisions matter. Focused on automation organizations can defend, not just deploy. [More from Tim](https://aletyx.ai/authors/tim-wuthenow/) --- # Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI Source: https://aletyx.ai/events/aletyx-at-decisioncamp-2025/ [Events & Community](https://aletyx.ai/topics/events-and-community/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [DMN](https://aletyx.ai/topics/dmn/) January 15, 2025 3 min ![Warm orange and blue lights in a conference venue](https://aletyx.ai/_astro/event-hero.BKDNyS92_2jk063.webp) Published January 15, 2025 **[ Join Aletyx at DecisionCAMP 2025](https://decisioncamp2025.wordpress.com/registration/)** and learn how to solve GenAI’s reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. --- Most enterprises exploring AI to win the innovation race, get stuck and unable to progress on their projects, with 95% of AI pilots never getting to production. In DecisionCAMP 2025 you can explore winning strategies for business intelligence requires an architecture that supports innovation and guarantees compliance. Join us and confidently push into production, the best out of AI innovations for decision making solutions, by learning how enterprise architecture in **Decision Intelligence** can **Turn Decisions into Agents** . > How can architects align powerful AI features with core business logic in **compliant,** **traceable**, **auditable** manners? How to keep policies **safe** from the risks of hallucinations? We understand that mission-critical systems can’t rely on “almost right” results, unpredictable outputs, and can’t be a complete black box for teams. To answer these pain points, we’ll present online, a [session](https://decisioncamp2025.wordpress.com/program/#AlexPorcelli) that explains how architects can easily design intelligent decision solutions with NeuroSymbolic AI. Discover how to combine [Symbolic AI and GenAI](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/), to overcome the limitations of LLMs. --- ### **Aletyx at DecisionCAMP** 2025: Virtual Event **in September** We invite you to a deep dive into the future of enterprise decision intelligence, on **September 23rd**, at **DecisionCAMP 2025**. **Turning Decisions into Agents: DMN Meets GenA** I 📅 **Tuesday**, **September 23** at **11:00 AM EDT** 📍 **Virtual** (Online – Join from anywhere!) 🚀 **[Click here to Register for](https://decisioncamp2025.wordpress.com/registration/) [FREE](https://decisioncamp2025.wordpress.com/registration/)[!](https://decisioncamp2025.wordpress.com/registration/)** 🚀 This is must watch session for automation experts, developers and architects tasked with pushing AI innovation into production. We’ll share insights to help you unlock a safe path for creating intelligent enterprise solutions backed by guardrails, the rules you trust. Understand the hybrid architecture that bridges Symbolic AI (with DMN, Drools, and MCP) with **GenAI** tools (e.g. Claude, ChatGPT, Gemini, etc ), and how it accelerates teams by improving collaboration. The speaker, **[Alex Porcelli](https://www.linkedin.com/in/alexporcelli/)**, brings a solid background of nearly 30 years in development and over 15 years as a core contributor and leader in the Apache KIE (Drools, jBPM, Kogito) ecosystem, Alex brings unparalleled expertise in building scalable, open-source process and decision automation and AI solutions. [![Aletyx session at DecisionCAMP's Agenda](https://aletyx.ai/_astro/alex-dcamp2025-session.FFNl-TF6_MhweF.webp)](https://decisioncamp2025.wordpress.com/program/#AlexPorcelli) We look forward to having you in our session, *see you there!* 🔥 --- ### **We Support DecisionCAMP** Since 2008, DecisionCAMP has been the hub for experts in Business Rules, Machine Learning, and Optimization. As the focus shifts to the practical application of GenAI, there is no better place to share the architectural foundations that will define the next generation of enterprise AI. Aletyx leads solutions in enterprise decision intelligence. While we fully dedicated to the [unique, high quality experience and journey of our clients](https://aletyx.ai/consulting/), we proudly support the evolution of the technology and its broader community ecosystem. That’s why, [we are proud](https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/ "DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence") [sponsors of DecisionCAMP 2025](https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/ "DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence"). --- # Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025 Source: https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/ [Events & Community](https://aletyx.ai/topics/events-and-community/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) April 15, 2025 2 min ![A close-up of source code displayed on a laptop](https://aletyx.ai/_astro/laptop-with-code.CvW-e5mA_r3c9t.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published April 15, 2025 At the recent Arc of AI Conference held from March 31 to April 3, 2025, in Austin, Texas, Aletyx’s co-founder, Alex Porcelli, delivered a compelling presentation titled “Smarter AI: Combining LLMs and Rule Engines for Safer and Predictable Results.” The session attracted a good audience and received very positive feedback, underscoring the relevance and timeliness of the topic. Alex’s talk delved into the integration of Large Language Models (LLMs) with Symbolic AI, emphasizing the synergy between Generative AI and Decision Model and Notation (DMN). He highlighted how this combination can lead to more reliable and interpretable AI systems, addressing common concerns about the unpredictability of LLM outputs. While the presentation was not officially recorded at the conference, Aletyx has made a replay available for those interested in exploring these insights further. Coming soon: you’ll be able to watch a recording – [follow our events page](https://aletyx.ai/events/) to get updated! The Arc of AI Conference featured over 40 distinguished speakers, including several thought leaders in the field, making it a premier platform for software developers, architects, data engineers, and technology leaders to explore and accelerate advancements in AI and machine learning. Alex expressed his appreciation for being part of such an esteemed gathering: > It was an honor to share the Arc of AI stage with so many bright minds and thought leaders in the field and share a bit of somewhat new perspective on how to tame the LLM using rule engines. For more information about the conference and its sessions, visit the [Arc of AI Conference website](https://www.arcofai.com/). ## References 1. [Arc of AI Conference](https://www.arcofai.com/) — Arc of AI ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI_dev Europe 2025 Source: https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/ [Events & Community](https://aletyx.ai/topics/events-and-community/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [DMN](https://aletyx.ai/topics/dmn/) September 19, 2025 3 min ![A glowing light bulb on a dark wooden surface](https://aletyx.ai/_astro/glowing-light-bulb.BJiTEkAc_7nNi2.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) and [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Published September 19, 2025 Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. In [this tech talk](https://aletyx.ai/events/aletyx-at-ai_dev-2025/), [Tim Wuthenow](https://www.linkedin.com/in/timwuthenow/) and [Alex Porcelli](https://www.linkedin.com/in/alexporcelli/) address a critical enterprise challenge: the fact that GenAI is statistically correct, but often **situationally wrong**. This lack of accuracy creates significant risks in high-stakes scenarios. This tech talk covers a practical hybrid AI architecture that integrates the flexibility of LLMs with the precision of open-source standards like **DMN and Drools**. The talk demonstrated how this approach allows you to update AI reasoning in real-time, creating an intelligent system that is not only compliant but also instantly adaptable to changing business policies. [Video: Architecting the AI Bridge: Integrating LLMs and DMN With Drools and SpringBoot by Tim Wuthenow & Alex Porcelli](https://www.youtube.com/embed/-hemGXHpKh0?si=rSEJc6QJbsKxEKwl) This session was presented on August 2025, at the AI\_dev Summit held in Amsterdam. ### Takeaways ✍️ - **Why GenAI Fails in Production** Statistical correctness ≠ situational correctness. The talk explores the risks of relying solely on probabilistic models for critical decisions made by systems. - **The Power of a Hybrid Approach** How to use the **Model Context Protocol (MCP)** to seamlessly connect LLMs (GenAI, like Claude Code) to Symbolic AI that follows a deterministic approach. In this case, policies determined using **DMN decisions**, executed by **Drools** and made readily available for integration with Claude. - **Instant Adaptation & Auditability** This hybrid AI architecture allows you to modify the business policies and logic that guardrails AI execution *in real-time*, without model retraining. Additionally it maintains a full, explainable audit trail. - **Live Demo** – AI-Driven Clinical Decision Support (AI-CDS): A demonstration of an AI-enhanced solution that shows the difference between traditional GenAI usage compared to the combined guardrails of Symbolic AI. An AI CDS provides smarter, faster, and personalized recommendations for better decision-making by healthcare practitioners and patients. ### About the Speakers 🎤 **[Alex Porcelli](https://www.linkedin.com/in/alexporcelli/):** A seasoned architect with over 25 years of experience. A long-time open-source advocate and contributor to Drools, jBPM, and Kogito for over 15 years. **[Tim Wuthenow](https://www.linkedin.com/in/timwuthenow/):** An enterprise AI architect with 15+ years in business automation at IBM and Red Hat. Specialized in integrating rule engines with AI for compliant, explainable systems. ## Resources & Links 🔗 **Get the Slides:** Architecting the AI Bridge, by Aletyx at AI\_Dev Europe 2025 ([Download](https://aletyx.ai/assets/aletyx-ai_dev-2025.pdf)). 🤩 **Learn more** about [Aletyx build of Drools](https://aletyx.ai/enterprise-drools/). 🚀 **Ask for a Demo:** See how our enterprise-grade Drools, Kogito, and DMN solutions, backed by built-in AI, can help your business scale GenAI with confidence. [Get in touch](https://aletyx.ai/contact/), we’ll be happy to expand on your ideas. --- *Couldn’t make it to AI\_dev Europe? Explore other events and tech talks, and get to know about upcoming events [here](https://aletyx.ai/events/).* ## About the authors [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) [Tim Wuthenow](https://aletyx.ai/authors/tim-wuthenow/) Co-founder & CCO More than 15 years putting rules, process, and AI to work where enterprise decisions matter. Focused on automation organizations can defend, not just deploy. [More from Tim](https://aletyx.ai/authors/tim-wuthenow/) --- # Try a 60-Day Guided Pilot and discover predictable AI Source: https://aletyx.ai/free-trial/ Book your free trial Our architects will help you configure, migrate and validate your first use case. ## Evaluate Aletyx with support from our architects ### Deploy your enterprise build Enterprise builds of Drools, Kogito, jBPM, KIE Server and Decision Control. ### Onboard with our engineers A senior engineer will assist with the initial installation in your environment. ### Get priority support Priority access to our team for configuration questions during the pilot. [Talk to an Aletyx Architect](https://aletyx.ai/contact/) ## Try a free guided pilot and validate your first use case We respect the complexity of your environment. It’s no simple task to orchestrate decisions in Kubernetes or migrate critical legacy systems. That’s why our engineers are invested in the success of your pilot. [Talk to an Expert](https://aletyx.ai/contact/) --- # Automate mission-critical workflows with accountable AI Source: https://aletyx.ai/intelligent-process-automation/ Intelligent Process Automation Aletyx orchestrates your IT systems, people, and AI agents. Modernize legacy RHPAM, BAMOE v8, jBPM, and KIE Server workloads with zero rewrites, and build AI-native workflows that deliver safe and reliable outcomes. [Try a guided pilot](https://aletyx.ai/free-trial/) Watch a 2-minute overview Zero rewrites AI-native. Deterministic. Flat-fee pricing ## Your RHPAM or jBPM v7 platform has been abandoned — it’s a compliance liability Your jBPM v7 and KIE Server workflows have no upgrade path. IBM and Red Hat removed the v7 architecture from their roadmaps and expect you to rebuild from scratch. ### v7 never moved to Apache The legacy v7 codebase never moved to Apache. You run on a frozen, three-year-old snapshot with no roadmap and dozens of unpatched vulnerabilities. ### The official ‘upgrade’ is a rewrite IBM BAMOE v9 removes KIE Server entirely. To stay supported, you must migrate to Kogito and rewrite your code from scratch. ### AI needs a modern foundation You cannot build Agentic AI on Java 8. Being stuck on a legacy v7 runtime prevents you from integrating LLMs or meeting modern security standards. Why Aletyx ## Aletyx modernizes your workflows and protects your existing investments AI proposes action, but your workflows define the outcome. Aletyx integrates AI safely into your deterministic processes. Your core operations will remain stateful, auditable and firmly under your control [Try a guided pilot](https://aletyx.ai/free-trial/) You need a standard, drop-in workflow engine ### Upgrade KIE Server without a rewrite Aletyx provides a binary-compatible runtime that moves your legacy jBPM workloads to a secure, modern stack. You need to distribute workflows at scale ### Scale Kogito beyond community limits Our enterprise-exclusive Scalable Process shards stateful workflows across clusters for high-throughput order processing and business operations. AI agents need to trigger and participate in your workflows ### Orchestrate AI with deterministic rules The AI Agent Node integrates LLMs directly into your process flow. AI handles the reasoning while the workflow handles the state, execution and guardrails. Regulators or auditors require proof ### Prove compliance with total state history Historical logging eliminates black-box risks. Every execution is versioned and logged, which gives you evidence of human and AI processes for regulators. One platform. Two execution paths. ## Unify your enterprise workflows with one operating model Intelligent Process Automation is Decision Intelligence plus workflow execution. One platform with two integrated runtimes: deterministic decisions and stateful workflows, governed together for audit-ready automation. Two integrated runtimes ensure continuity for existing workloads and offer a forward path for new projects — with native AI at the core of both engines. For existing workflows For existing workflows ### Modernization: Upgrade your legacy jBPM and KIE Server workloads without rewrites Aletyx Enterprise Build of KIE Server is a drop-in replacement for RHPAM, BAMOE v8, and jBPM deployments. It delivers a modern, secure and AI-capable foundation yet preserves complete behavioral compatibility. - **Preserve existing behavior:** Your existing KJARs deploy directly onto a modern runtime with the exact same APIs, execution semantics, and process logic. - **Upgrade to a modern stack:** The updated architecture eliminates legacy dependencies, moving your workloads safely to Java 21, Jakarta EE 10, Spring Boot 3, and EAP 8.x. - **Enable native AI capabilities:** Model Context Protocol (MCP) triggers and AI Agent nodes allow direct LLM invocation. The exact same AI features shipping in Kogito are now accessible on KIE Server. - **Secure enterprise operations:** Active CVE patches, signed builds, controlled dependency baselines, and long-term support protect your critical infrastructure. [Explore Enterprise KIE Server](https://aletyx.ai/enterprise-kie-server/) ![jBPM logo](https://aletyx.ai/_astro/kie-logo.CHy-rmoz_1Fcxgk.webp) For new projects For new projects ### Orchestration: Deploy deterministic AI workflows at massive scale Aletyx Enterprise Build of Kogito delivers deterministic, AI-native execution and provides enterprise-exclusive scaling capabilities for new workflow projects. - **Embed AI at the engine level:** Model Context Protocol (MCP) integration and AI Agent nodes allow LLMs to safely execute intelligent tasks directly within your process flow. - **Guarantee deterministic execution:** Artificial intelligence informs the decision, but the workflow controls the action. Every execution remains guaranteed, recorded, and completely reproducible. - **Scale stateful processes horizontally:** Our enterprise-exclusive Scalable Process distributes workflow state and execution across your infrastructure. This high-throughput capability is completely unavailable in community versions. - **Schedule jobs across distributed clusters:** Multi-node job schedulers operate without leader election to ensure precise timer and deadline execution across distributed environments. [Explore Enterprise Kogito](https://aletyx.ai/enterprise-kogito/) ## Automation proposes action.Workflows guarantee outcomes. You’re under pressure to bring AI into core business operations. Agents can route, recommend and orchestrate. But the execution to trigger any payment, claim or trade must be deterministic. ### Risk obsolescence without Aletyx **Your workflow platform is abandoned.** No security patches. No upgrade path without a rewrite. AI capabilities are absent from your core operations. ### Modernize and scale with Aletyx **Workloads run on a modern, secure architecture.** Both legacy upgrades and new deployments are natively connected to AI agents via MCP. ### Example: **Review a compliance exception** **An AI agent identifies an anomaly and triggers a remediation workflow.** The workflow executes deterministically to escalate the issue, enforce approval gates and record the history. The agent coordinates the intelligence and the workflow guarantees the outcome. You don’t need to rewrite your workflows to add AI. You need a platform that brings AI to them. [Try a guided pilot](https://aletyx.ai/free-trial/) ## Built for the architect. Designed for the audit Move faster without losing control. Adopt AI without adding risk. Prove what happened when it matters. ### For the Platform Architect - Run on any cloud: Deploy across Kubernetes distributions and container orchestration platforms - Scale your way: Scale stateful workflows on Kogito, or deploy KIE Server on EAP and Spring Boot. - Integrate without lock-in: Fit into your CI/CD pipelines without proprietary deployment constraints - Build on open standards: Leverage BPMN, DMN, Jakarta EE, and MCP ### For the Executive Sponsor - Stand behind every execution: Maintain complete, replayable history for every workflow. - Modernize without a rewrite: Eliminate multi-quarter migration programs - Adopt AI without risk: Introduce intelligence without non-deterministic threats to core operations - Eliminate pricing surprises: Secure predictable, flat-fee pricing without per-process or per-core penalties A clear choice for enterprises ## Only Aletyx can deliver zero rewrites,native AI and flat pricing Consideration Aletyx IBM (BAMOE) Red Hat Apache KIE Server support Fully restored and modernized - v8 fast approaching EOL - removed in v9 End of life Not transferred to Apache Modernization approach Drop-in for existing, cloud-native for new - v8 fast approaching EOL - v9 requires full rewrite N/A Kogito only — no backward continuity AI capabilities Native on both runtimes: MCP, AI nodes, LLM Bolt-on None None Enterprise scaling Scalable Process (Kogito exclusive) Limited None Not available Security Active CVE patching on both runtimes v8 fast approaching EOL End of life No SLA, no patches Support Direct access to core engineers Tiered L1→L3 Unavailable Volunteer-based, no SLA Pricing Flat fee, predictable Per-core, yearly increases N/A Free (high internal cost) Consideration ### KIE Server support Aletyx Fully restored and modernized IBM (BAMOE) - v8 fast approaching EOL - removed in v9 Red Hat End of life Apache Not transferred to Apache Consideration ### Modernization approach Aletyx Drop-in for existing, cloud-native for new IBM (BAMOE) - v8 fast approaching EOL - v9 requires full rewrite Red Hat N/A Apache Kogito only — no backward continuity Consideration ### AI capabilities Aletyx Native on both runtimes: MCP, AI nodes, LLM IBM (BAMOE) Bolt-on Red Hat None Apache None Consideration ### Enterprise scaling Aletyx Scalable Process (Kogito exclusive) IBM (BAMOE) Limited Red Hat None Apache Not available Consideration ### Security Aletyx Active CVE patching on both runtimes IBM (BAMOE) v8 fast approaching EOL Red Hat End of life Apache No SLA, no patches Consideration ### Support Aletyx Direct access to core engineers IBM (BAMOE) Tiered L1→L3 Red Hat Unavailable Apache Volunteer-based, no SLA Consideration ### Pricing Aletyx Flat fee, predictable IBM (BAMOE) Per-core, yearly increases Red Hat N/A Apache Free (high internal cost) Your last chance ## Try a free guided pilot and explore safe generative AI Let’s talk about how Aletyx can modernize your KIE Server workloads. Our architects are ready to help you. [Try a guided pilot](https://aletyx.ai/free-trial/) --- # Modernize Drools & jBPM without a rewrite Source: https://aletyx.ai/modernization/ If it runs on Drools or KIE Server, it runs on Aletyx Aletyx is the only zero-rewrite path to modernize your logic and enable AI. Upgrade to a cloud-native stack that preserves your business logic and delivers the security and scale required for compliance-heavy sectors and mission-critical operations. [Request free migration assessment](https://aletyx.ai/contact/) Zero rewrites Drop-in modernization Fixed pricing The risk of legacy automation ## Your decisions and workflows are trapped on legacy infrastructure Your core business automation runs on borrowed time. Legacy Drools and jBPM power your pricing, eligibility and risk. But the ecosystem has stalled. You rely on unpatched ‘abandonware’ that exposes you to audit failure. Your only official solution is an expensive rewrite. ### Exposure to outdated community releases Community releases for Drools and jBPM are years behind. You run core business logic on volunteer snapshots with no security patches or roadmap. ### Costly forced rewrites for KIE Server & BAMOE The IBM upgrade path forces you to abandon KIE Server. You face a full rewrite to Kogito that will cost millions in migration fees and regression testing. ### Compliance failure from unpatched CVEs Legacy stacks trap you on Java 8 and WildFly. This exposes your workflows to dozens of ‘High’ and ‘Critical’ vulnerabilities that will trigger audit failures. ### Operational risk from declining patch velocity Vendor support has evaporated. With IBM’s focus shifting and Red Hat’s maintenance ending, your production systems face declining patch velocity ### One single incident could cost more than an annual support fee Log4j proved the danger of hidden dependencies. Modernization is not just about new features. It’s about preventing the next crisis before it strikes. [Talk to an Aletyx Architect](https://aletyx.ai/contact/) The Aletyx solution ## Modernize your decisions and workflows with the original architects We are the original team behind Drools and jBPM. Aletyx is the natural continuation of the platform. We offer the only path to modern 10.x capabilities and AI-native automation without the cost of a rewrite. Simply replace your existing runtimes with: Aletyx Enterprise build of Drools Aletyx Enterprise build of KIE Server ### Zero-rewrite migration Retain your decision logic when you migrate. No breaking changes or 12-month refactoring projects. ### Predictable pricing Scale your processors and containers without being penalized for your success thanks to our ‘flat fee’ model. ### Long-term security Protect your critical systems with active security monitoring, patches and vulnerability tracking (CVEs). ## Zero-rewrite migration in three steps ### Non-intrusive diagnostics Our tools analyze your current KIE/Drools repositories to map dependencies and versions. ### Runtime swap We replace outdated runtimes with the Aletyx Enterprise Runtime. Your code remains untouched. ### Regression testing We test your workloads to guarantee they execute with the exact same deterministic behavior. [Request free migration assessment](https://aletyx.ai/contact/) The v10.x upgrade trap ## The standard upgrade path to 10.x will force a total rewrite Any move to the modern stack via Community or IBM will require you to rebuild your application logic and your runtime infrastructure. ### Drools 10.x breaks BPMN orchestration Community Drools broke BPMN-based rule flows. If you use startProcess or .rf files to sequence your rules, a direct upgrade will break your code and force an architectural redesign. ### KIE Server has been abandoned The community replaced KIE Server with Kogito, which uses different APIs and execution semantics. There is no upgrade path — only a requirement to rewrite your integration code and replace your runtimes. [See how Aletyx preserves these capabilities See how Aletyx preserves capabilities](https://aletyx.ai/contact/) The zero-rewrite solution ## Aletyx fixes your technical debt, without creating migration debt. Swap your runtime, not your code. Aletyx offers the only modernized runtime that's fully compatible with your v7 assets and clears these critical CVEs, the moment you deploy. High / Critical vulnerabilities ### Red Hat PAM/DM vulnerabilities Multiple known CVEs No longer under active development [View CVE Details](https://kiecve.aletyx.ai/?version=7.67.0.Final-redhat-00029) High / Critical vulnerabilities ### Community Drools/jBPM vulnerabilities Multiple known CVEs Limited patch velocity [View CVE Details](https://kiecve.aletyx.ai/?version=7.74.1.Final) Modernize Drools v7 and v8 without rewrites ## Orchestrate rules 30x faster, without a rewrite Any move from Drools v7 or v8 to Community Drools 10.x will break your rules and orchestration. Aletyx restores full compatibility and optimizes the engine to execute your existing flows up to 30x faster than the community alternative—no rewrite required. [Request free migration assessment](https://aletyx.ai/contact/) ![Speedometer showing 30x faster rule orchestration with Aletyx](https://aletyx.ai/_astro/speed.DJN9d12i_Zh3HKT.webp) Drop-in KIE Server modernization ## Modernize your KIE Server to Java 21 The community abandoned KIE Server for Kogito and left you stuck on old tech. Aletyx re-platformed the KIE server so you can run your existing jBPM workloads on a cloud-native Java 21 and Spring Boot 3 architecture—this instantly secures your stack without changing your integrations. [Request free migration assessment](https://aletyx.ai/contact/) ![Shield representing modernized KIE Server security on Java 21](https://aletyx.ai/_astro/shield.DUB7vFyY_ZmcINa.webp) Accountable agentic AI ## Turn your legacy logic into accountable AI workflows Trust is the biggest challenge for enterprise AI. Aletyx combines the flexibility of GenAI with reliable execution, based on native decisions and workflows that govern your AI and keep it predictable. ### Flexible GenAI Use LLMs to parse documents, summarize messy data and handle complex customer interactions. ### Predictable decisions Use your Drools logic to validate every AI proposal and ensure that business policies are always obeyed. ### Reliable workflows Use KIE Server to coordinate the safe handoff between AI agents, automated rules and human experts. [Learn more](https://aletyx.ai/contact/) Global enterprises trust Aletyx ## Our founders' code has powered the global economy for nearly 20 years Now Aletyx founders and engineers support the world’s largest organizations as you transition to AI-native, modern intelligence automation. Global finance Fortune 500 institutions. Manufacturing Major medical device manufacturers. Retail Global giants across Europe. ### Financial services Powers the US mortgage market and real-time fraud detection. Banks process millions of transactions with millisecond latency and 100% compliance. ### Insurance Orchestrates complex claims journeys. Insurers reduce cycle times from days to seconds and maintain a perfect audit trail for every approval or rejection. ### Healthcare/logistics Manages patient journeys and global supply chains. We coordinate operations where failure is not an option: from clinical support to retail edge. [Learn more](https://aletyx.ai/contact/) A clear choice for enterprises ## Only Aletyx can deliver zero rewrites, flat pricing and founder-led support Consideration Aletyx IBM (BAMOE) Red Hat Apache Modernization approach Zero rewrite, compatibility restored v8 support ends 2027; v9 requires rewrite Transferred to IBM (2022) Forward evolution, not backward continuity Compatibility across versions Continuity preserved across generations Breaking changes between v8 and v9 V7.x lifecycle only Breaking changes expected KIE Server support Fully restored and modernized Included in v8, removed in v9 V7.x lifecycle only Not transferred to Apache Security and maintenance Active vulnerability tracking and patching v8 support through 2027 No active development Community driven, no SLA Support model Direct access to core engineers, enterprise SLAs Tiered L1 to L3 escalation No longer available Volunteer-based, no SLA Pricing model Flat fee per tier, predictable growth Per core pricing, high water mark, yearly increases N/A No license, high internal cost AI readiness Native and independent AI integration AI capabilities tied to IBM portfolio No active development Build it yourself Consideration ### Modernization approach Aletyx Zero rewrite, compatibility restored IBM (BAMOE) v8 support ends 2027; v9 requires rewrite Red Hat Transferred to IBM (2022) Apache Forward evolution, not backward continuity Consideration ### Compatibility across versions Aletyx Continuity preserved across generations IBM (BAMOE) Breaking changes between v8 and v9 Red Hat V7.x lifecycle only Apache Breaking changes expected Consideration ### KIE Server support Aletyx Fully restored and modernized IBM (BAMOE) Included in v8, removed in v9 Red Hat V7.x lifecycle only Apache Not transferred to Apache Consideration ### Security and maintenance Aletyx Active vulnerability tracking and patching IBM (BAMOE) v8 support through 2027 Red Hat No active development Apache Community driven, no SLA Consideration ### Support model Aletyx Direct access to core engineers, enterprise SLAs IBM (BAMOE) Tiered L1 to L3 escalation Red Hat No longer available Apache Volunteer-based, no SLA Consideration ### Pricing model Aletyx Flat fee per tier, predictable growth IBM (BAMOE) Per core pricing, high water mark, yearly increases Red Hat N/A Apache No license, high internal cost Consideration ### AI readiness Aletyx Native and independent AI integration IBM (BAMOE) AI capabilities tied to IBM portfolio Red Hat No active development Apache Build it yourself [Get My Zero Rewrite Migration Plan](https://aletyx.ai/contact/) Your last chance ## Try a free guided pilot and unlock accountable AI Let's talk about how Aletyx can modernize your Drools & jBPM. Our architects are ready to help you. [Talk to a specialist](https://aletyx.ai/contact/) Frequently asked questions ## Any questions? Get a clear answer from our architects. [Get my assessment report](https://aletyx.ai/contact/) 01 Can Aletyx modernize our existing Drools and jBPM workloads without rewrites? Yes. Aletyx is built for continuity across prior-generation production workloads so you can modernize without refactoring business logic. 02 What happens with KIE Server, since IBM and Apache do not include it? Aletyx Enterprise Build of KIE Server is a drop-in replacement that runs on Java 21, Jakarta EE, Spring Boot 3, and a modern application server. Your existing architecture, integrations, and behavior remain unchanged. 03 How does Aletyx reduce our security and vulnerability exposure? Aletyx actively tracks and patches vulnerabilities across its builds, unlike community or end-of-life platforms that may have hundreds of unresolved CVEs. 04 If I want the latest Apache 10.x capabilities from Drools or Kogito, does Aletyx include them? Yes. Aletyx Enterprise Build of Drools delivers all the capabilities offered in Drools 10.x while restoring compatibility for v7 and v8 workloads, including up to 30x faster rules orchestration. 05 Do you offer enterprise SLAs and 24 by 7 support? Yes. Aletyx provides direct access to core engineers with Red Hat-level support, including enterprise SLAs and around-the-clock availability. 06 What does an assessment actually involve? Our team maps your specific workloads, dependencies, and integrations to provide a clear migration plan with zero rewrites. The initial assessment is free. --- # Mortgage AI governance that stands up to review Source: https://aletyx.ai/mortgage-ai-governance/ Mortgage AI governance Fannie Mae and Freddie Mac are requiring AI governance regardless of origination channel, third-party service provider, or other mortgage operations. Aletyx turns that guidance into explainable decision services and AI guardrails, with approval, versioning, and retrievable audit trails built in. [Discuss mortgage AI governance](https://aletyx.ai/mortgage-ai-governance/contact/) [See the requirements](https://aletyx.ai/mortgage-ai-governance/#requirements) Aletyx governed decision layer ## Guidance becomes an executable control Audit trail built in 01 **Guidance** Fannie Mae, Freddie Mac, servicing policy, and internal controls. 02 **Decision model** Reviewable decision tables, workflows, and test cases. 03 **Controlled publish** Approvals, versions, environments, and release history. 04 **Execution** Applications, agents, vendor workflows, and guardrails call the same governed decision. 2026 Fannie and Freddie guidance ## What changed for mortgage AI in 2026? The new guidance turns AI from an innovation program into an accountable operating control. The lender or servicer of record needs evidence across origination, servicing, third-party service providers, and every loan origination channel where AI is used. Freddie Mac [Source](https://guide.freddiemac.com/app/guide/section/1302.8) ### Bulletin 2025-16: Seller/Servicer Guide Section 1302.8 Effective March 3, 2026 Requires Seller/Servicers to govern AI and machine learning used in origination and servicing, including senior management approval, annual policy review, prompt disclosure, monitoring, audits, bias/security checks, segregation of duties, and oversight across all channels of loan origination. Fannie Mae [Source](https://singlefamily.fanniemae.com/news-events/lender-letter-ll-2026-04-governance-framework-use-artificial-intelligence-and-machine-learning) ### Lender Letter LL-2026-04 Published April 8, 2026. Effective August 6, 2026 Requires seller/servicers using AI or machine learning in origination or servicing to maintain policies and procedures, manage AI risk, address trustworthy and ethical use, govern subcontractor and vendor AI, and disclose AI use on request. Mortgage channel reality ### Multiple Channels. One accountable lender. AI decisions may happen inside the lender, at a broker, through a correspondent, with a contract underwriter, or inside a vendor platform. The obligation still rolls back to the lender or servicer of record. - #### Retail Loan officers and operations teams use AI for pricing, income, fraud, conditions, or exception routing. - #### Wholesale (TPO) Broker submissions can apply lender guidance differently before underwriting or post-close review detects the issue. - #### Correspondent The lender remains accountable for loans acquired through correspondent books, including repurchase exposure. - #### Contract underwriting External underwriters make credit decisions that define the lender's regulatory position and exception patterns. - #### Vendor platforms Title, appraisal, income, flood, and other services may embed AI the lender does not directly control. Accountability point Aletyx turns distributed AI activity into a defensible record: channel, inputs, policy version, decision result, owner, approval path, and monitoring evidence. Review readiness ## When review comes, can you produce the file? Mortgage AI governance is not proven by a policy document alone. Lenders need decision-level evidence before a GSE, investor, examiner, or internal risk team asks for it. Evidence lenders will be asked to show - Pre-deployment testing - Adverse-action rationale - Post-deployment monitoring - Third-party AI oversight - Named senior accountability Governance surface ## What must mortgage lenders be able to prove? AI governance does not stop at a model inventory or inside the lender's four walls. The hard part is connecting each channel's decision, workflow, approval, vendor, and production record to policy the lender can defend. ### Policies and ownership Document how AI and machine learning are developed, implemented, used, maintained, reviewed, and owned across mortgage operations. ### Risk controls Map, measure, and manage AI risk based on legal requirements, risk tolerance, security expectations, and fair lending obligations. ### Channel accountability Prove governance for AI used by retail teams, brokers, correspondents, contract underwriters, and vendors, not only systems the lender directly controls. ### Audit evidence Keep a record of the inputs, rule version, decision result, approval path, and effective date behind each governed decision. ### Segregation of duties Separate the people who author, approve, deploy, and monitor decision logic so control is visible and enforceable. ### Ongoing monitoring Review AI-assisted systems for performance, security, bias, vulnerabilities, and deviations from approved policy. ### Vendor AI oversight When third-party AI tools are called through governed workflows, record the interaction, apply controls to the outcome, and maintain an audit trail of what was sent and returned. Lifecycle coverage ## Where does AI governance show up in the mortgage lifecycle? The first project may start in origination, but the same accountability pattern applies anywhere AI or automation influences a loan-level outcome, regardless of channel, vendor, exception, communication, or handoff. Lifecycle area Decision to govern Evidence Aletyx can preserve Origination and underwriting Eligibility, income treatment, AUS overlays, condition routing, exception approval Guideline version, borrower inputs, decision table result, reviewer action, publish history Servicing and loss mitigation Forbearance, repayment plan, modification routing, fee application, notice timing Servicing rule version, borrower status, timeline, escalation record, approval owner Quality control and post-close review Pre-fund checks, post-close defect investigation, repurchase response, pattern analysis Original rule execution, exception record, defect mapping, impacted loan population Secondary marketing and delivery Pricing adjustments, lock exceptions, delivery eligibility, investor routing Pricing rule version, lock-time inputs, exception approver, delivery rationale Valuation and appraisal workflow Waiver eligibility, AVM-assisted routing, desktop appraisal acceptance, review exceptions Valuation inputs, model output, acceptance rule, reviewer decision, timestamp Third-party channels and vendors Broker guidance use, correspondent submissions, contract underwriting, title, appraisal, income, or flood service decisions Channel or vendor owner, policy version, decision inputs, exception path, oversight record Aletyx approach ## How does Aletyx turn mortgage guidance into governed decisions? Aletyx is not a loan origination system or servicing platform. It is the governed decision and workflow layer that sits beside loan origination, servicing, agent, and vendor workflows to make policy execution traceable, testable, and auditable. 01 ### Turn guidance into a decision model Aletyx AI Assistant helps translate investor guidance, lender overlays, servicing policies, and compliance rules into decision models and workflows that humans can review. 02 ### Review the model before it runs Policy owners, compliance teams, and engineers can inspect the logic as decision tables, test cases, workflows, and versioned changes before anything is published. 03 ### Publish controlled decision services Approved models run as governed services for loan origination, servicing, vendor oversight, quality control, pricing, or compliance systems, with environment controls and release history. 04 ### Expose the same decision as an agent skill The same approved decision can be invoked by agents through skills, or used as a guardrail pattern in large language model pipelines, including NVIDIA NeMo based architectures. [QCon AI Boston 2026 session](https://boston.qcon.ai/presentation/boston2026/decision-models-agentic-architectures-production-agent-skills) ![Aletyx governance dashboard showing controlled decision management](https://aletyx.ai/_astro/governance-dashboard.D82IY55Y_Ye07.webp) Agentic architecture ## Why use decision models instead of asking a large language model to decide? Mortgage AI works best when probabilistic AI handles ambiguity and deterministic models handle accountable decisions. That separation is what makes agentic systems usable in regulated workflows. Governance concern Large language model only Aletyx decision model pattern Guideline interpretation A model may summarize guidance, but the result can vary across prompts and model versions.Guidance is modeled as explicit decision logic with reviewable rules, tests, and version control. Loan-level execution The system may answer a question, but proving the exact policy path can be difficult.Each execution ties internal or third-party inputs to a decision result, rule version, timestamp, and audit trail. Agent behavior An agent can reason through a scenario, but high-stakes outcomes remain probabilistic.The agent gathers context, then calls a deterministic decision model for the governed result. Regulatory change Policy updates can be scattered across prompts, code, documents, and manual checklists.Changed obligations become targeted model changes with approvals, tests, and controlled publishing. Audit record ## Every AI-assisted decision needs an evidence trail The evidence trail has to be created as the decision runs, not rebuilt after a review request. When a reviewer asks why a loan, borrower, file, or exception was handled a certain way, the answer should come from the system of record. - Which policy or guideline was in force at the time - Which borrower, loan, servicing, or investor inputs were evaluated - Which rule, decision table, or workflow path produced the result or adverse-action rationale - Who authored, reviewed, approved, and deployed the change - How the decision was tested before release - What monitoring, vendor oversight, or escalation followed production use ![Aletyx traceability view showing decision-level evidence](https://aletyx.ai/_astro/traceability.B51L_6qI_Zj4AFB.webp) FAQ ## Mortgage AI governance questions Short answers for lenders evaluating how to operationalize AI governance. [Talk to Aletyx](https://aletyx.ai/mortgage-ai-governance/contact/) 01 What is mortgage AI governance? Mortgage AI governance is the set of policies, controls, review processes, audit records, and risk management practices that govern AI used in mortgage origination, servicing, and related workflows. For lenders, the practical question is whether every AI-assisted decision can be explained, tested, approved, monitored, and defended later. 02 Do the Fannie Mae and Freddie Mac AI requirements apply only to origination? No. Fannie Mae LL-2026-04 and Freddie Mac Seller/Servicer Guide Section 1302.8 both address AI use connected to origination and servicing. That makes servicing, loss mitigation, borrower communication, quality control, and related operational decisioning part of the governance conversation when AI is used. 03 How does Aletyx help with explainable AI in mortgage lending? Aletyx separates deterministic policy decisions from probabilistic AI behavior. AI can help interpret documents, gather context, or assist with model authoring, but the governed outcome is produced by an explicit decision model or workflow with versioning, tests, approvals, and execution records. 04 Can Aletyx govern AI agents used by loan officers or operations teams? Yes. A mortgage agent can collect context from documents and systems, then call an Aletyx decision model as a skill for the final governed answer. The agent handles ambiguity, while the decision model handles the policy decision that must be consistent and auditable. 05 Where should a mortgage lender start? Start with one decision that is high-volume, rules-driven, and audit-sensitive, especially where accountability crosses a channel boundary: an underwriting overlay, contract underwriting exception, correspondent review, loss mitigation routing step, pricing exception, or quality control defect response. Model that decision, test it, publish it behind approvals, and use the audit trail as the operating pattern for the next decision. The Aletyx AI Assistant can accelerate onboarding by helping translate guidance documents into reviewable decision models. --- # Aletyx and Athena Decision Systems Announce Strategic Partnership Source: https://aletyx.ai/news/aletyx-and-athena-decision-systems-announce-strategic-partnership/ [Partnerships](https://aletyx.ai/topics/partnerships/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) September 15, 2025 2 min ![Two people shaking hands in front of a business chart](https://aletyx.ai/_astro/partnership.C8t5cXZX_NmI0I.webp) Published September 15, 2025 At Aletyx, we believe that successful decision automation requires both powerful technology and experienced hands to deliver it. That’s why we’re excited to announce our new strategic partnership with Athena Decision Systems. As part of this collaboration, Athena Decision Systems will represent Aletyx’s offerings across Europe, providing enterprises with direct access to the full benefits of our Enterprise build of Drools and Kogito. This includes long-term support, native agentic AI integration through the Model Context Protocol (MCP), and a roadmap focused on enabling hybrid AI decisioning systems. While Aletyx brings enterprise-grade technology based on open-source, the Athena team brings decades of hands-on experience designing and implementing high-impact decision automation solutions. Their trusted presence in the region and deep knowledge of decisioning practices make them the ideal partner to help organizations scale confidently and efficiently. > “Business rules are essential for accountable decisioning and mission-critical enterprise operations, and Aletyx delivers them with enterprise-grade power. We are excited to be collaborating with Aletyx for delivering solutions to European customers,” says Harley Davis, founder and CEO of Athena Decision Systems. > “We’re excited to work with a partner that knows the decision automation space inside and out,” said Alex Porcelli, Co‑founder of Aletyx. “This partnership strengthens Aletyx’s presence in Europe and combines our enterprise-ready technology with Athena’s hands-on delivery expertise. It’s a powerful combination for organizations ready to take the next step in modernizing their decisioning architecture.” With Athena as our strategic partner, we’re expanding our reach and ensuring European customers can adopt Aletyx technology with the guidance, support, and expertise they need. Together, we aim to drive the future of scalable, explainable, and agentic AI decision systems – one project at a time. Stay tuned for more as this partnership grows. For more information about this partnership or to explore how we can support your decision automation initiatives, reach out to our teams: ### Aletyx 📧 [contact@aletyx.com](mailto:contact@aletyx.com) 🌐 [aletyx.ai](https://aletyx.ai/) ### Athena Decision Systems 📧 [contact@athenadecisions.com](mailto:contact@athenadecisions.com) 🌐 [athenadecisions.com](https://www.athenadecisions.com/) --- # Announcing Aletyx Decision Control Sandbox on AWS Marketplace Source: https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/ [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Decision Intelligence](https://aletyx.ai/topics/decision-intelligence/) December 12, 2025 3 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) Published December 12, 2025 **Decision Control is now available on AWS Marketplace!** [Unlock your free trial and experience decision intelligence today](https://aws.amazon.com/marketplace/pp/prodview-weakaemafiris). **The problem we set out to solve** We kept hearing the same story. “I understood DMN. I built a model over the weekend. But we’re not a Java shop, so we had no way to actually use it.” Decision Model and Notation (DMN) is a powerful open standard created to empower decision analysts and engineers to model real-world business policies and rules. From healthcare to finance, DMN has been used to automate critical decisions at the center of business operations. In the mortgage domain, for instance, MISMO [1](https://www.mismo.org/) is formally adopting decision automation with DMN as their trusted solution to accelerate decision making. However, operationalizing decision logic proved to be a big challenge. The technical effort required to publish and run automated decisions introduced friction that slowed teams and limited the speed and adaptability that decision modeling was meant to deliver. That complexity creates a wall between the people who understand the business problem and the ability to solve it. The good news is: we heard you. **Experience the power of Aletyx Decision Intelligence.** Frictionless automation powered by AI, on AWS, ready to use in a matter of minutes. [Start Your Free Trial Today!](https://aws.amazon.com/marketplace/pp/prodview-weakaemafiris) **We heard you, and this changes today.** ## What’s in Decision Control Sandbox --- With Decision Control Sandbox, a few clicks is what you need to provision a complete decision automation platform. In minutes, you can start modeling, publishing and running your decisions powered by AI and built with the open standard of DMN. > *No Quarkus configuration. No Kubernetes management. No CI/CD pipelines to build.* Your decision models become REST APIs automatically, allowing you to focus on logic, not infrastructure. ### Key Capabilities --- Innovative and exclusive AI-powered features, designed to accelerate your proof-of-concepts and development cycles: - Five minute deployment from AWS Marketplace to operational decision service - Native Model Context Protocol (MCP) server for AI integration and policy enforcement - Full DMN 1.5 support with visual editor and FEEL expressions - One button publishing of new decision models for use across various domains - Concurrent execution of multiple decisions and versions across domains - Decision tracing with cross-version result comparison - Hourly billing with a 10 day free trial to try it out risk-free in your AWS environment ### A Platform Where Business Users Succeed --- Decision Control is designed to let the people closest to the problem model, test, and publish decisions without waiting for infrastructure work. The technical complexity disappears so the decision logic can do what it was always meant to do: drive real outcomes. #### Enterprise Decision Intelligence on AWS --- The Sandbox Edition is offered on AWS with resource optimizations targeted for development purposes only. Aletyx Decision Control is powerful and trusted to be at the core of enterprise mission-critical operations, with advanced features not available on the Sandbox, such as high availability, automated backups, SLA backed support, and data persistence. These, and many more innovations are included on Aletyx Decision Control (*Soon on AWS Marketplace*). ## Get Started Today --- If you have a decision model and nowhere to run it, or if you are looking to modernize your decision automation stack without the overhead, the Sandbox is ready for you. [**Start Free Trial on AWS**](https://aws.amazon.com/marketplace/pp/prodview-weakaemafiris) [**Read Documentation**](https://aletyx.ai/docs/decision-control/overview) *If AWS isn’t the environment you’re looking for, Decision Control can run wherever your infrastructure lives. [Let’s connect](https://aletyx.ai/contact/) and explore your next step to unlock smarter decisions.* --- # Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation Source: https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/ [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Drools](https://aletyx.ai/topics/drools/) April 22, 2025 3 min ![A close-up of source code displayed on a laptop](https://aletyx.ai/_astro/laptop-with-code.CvW-e5mA_r3c9t.webp) Published April 22, 2025 Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. **\[April 22, 2025\]** – Today, **Aletyx**, a new company founded by leading contributors of the Apache KIE ecosystem, officially launches with a mission to deliver enterprise-grade automation intelligence grounded in open-source technologies. Aletyx debuts with two flagship offerings: the **Aletyx Enterprise build of Drools** and the **Aletyx Enterprise build of Kogito**, designed to empower organizations with safer AI integration, cloud-native scalability, and expert-driven support. Since the transition of Drools and Kogito from Red Hat, the community has lacked a dedicated, open-source-savvy organization that not only understands the technology but also excels at delivering real-world value and knowledge to its users. Aletyx steps into this role—filling the gap with a mission to support both the open-source community and enterprise users with world-class tools and expertise. At the heart of the launch is Aletyx’s exclusive support for the **MCP protocol**, a groundbreaking [feature available in its enterprise](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) build of Drools. This integration enables users to instantly expose DMN (Decision Model and Notation) models to GenAI applications—transforming them into intelligent agents with built-in guardrails, **no fine-tuning, no hallucinations, and no risk**. > “With our enterprise builds, we’re giving organizations what they’ve been asking for: cloud-native performance and scalability with real AI innovative integration—backed by the same values that made open source thrive,” said **Alex Porcelli**, co-founder and long-time Apache KIE contributor. The **Aletyx Enterprise build of Kogito** further sets itself apart by solving one of the biggest limitations in cloud-native workflow engines: **scaling stateful services**. While the community edition of Kogito is optimized for the cloud, its scalability has been limited. Aletyx’s build unlocks **true horizontal scaling**, enabling stateful applications to seamlessly run across multiple pods without idle resource waste. In addition to its products, Aletyx offers **specialized training and consulting services** for Drools, jBPM, and Kogito—rooted in decades of hands-on implementation experience across enterprise environments. --- ## Founding Team - **Alex Porcelli** – 25+ years of career, almost 20 dedicated to open source. Apache KIE PPMC member, former engineering leader at Red Hat and IBM. - **Tim Wuthenow** – 10+ years in intelligent automation helping clients with hands-on experience around the globe. Led global tech sales for Drools/Kogito solutions. - **Eduardo Cerqueira** – 20+ years in DevOps and CI/CD. ASF member, Apache KIE committer and lead engineer in the Red Hat–IBM transition. --- ## Availability Aletyx Enterprise builds of Drools and Kogito are available now. Organizations can learn more and request a demo at [aletyx.ai](https://aletyx.ai/contact/). --- ## About Aletyx Aletyx specializes in intelligent automation solutions based on open-source technologies. With a strong foundation in the Apache KIE ecosystem, Aletyx delivers enterprise-ready builds of Drools and Kogito, backed by world-class support, training, and a commitment to safe, scalable GenAI integration. Aletyx is proud to continue its contributions to the open-source community while delivering the reliability enterprises need. **Press Contact** Aletyx Media Relations 📧 [press@aletyx.com](mailto:press@aletyx.com) 🌐 [aletyx.ai](https://aletyx.ai/) --- # Aletyx Officially Listed as Vendor of Apache KIE Source: https://aletyx.ai/news/aletyx-official-apache-kie-vendor/ [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Drools](https://aletyx.ai/topics/drools/) [Kogito](https://aletyx.ai/topics/kogito/) October 13, 2025 3 min ![An orange paper boat leading a group of white paper boats](https://aletyx.ai/_astro/paper-boat-leadership.KUYa_dzk_3PIAm.webp) By [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Published October 13, 2025 Aletyx is thrilled to announce our official listing as a vendor of Apache KIE technologies on the [Apache KIE commercial support page](https://kie.apache.org/docs/community/commercial-support/). This recognition reinforces our commitment to the Apache KIE open source ecosystem and the enterprises that rely on these technologies for mission-critical automation. ## Understanding Apache KIE [Apache KIE](https://kie.apache.org/) is an open source umbrella project hosted by the Apache Software Foundation. It unites mature automation technologies powering enterprise-scale business rules, processes, planning, and decision automation. Key projects include: - **[Drools](https://kie.apache.org/)** – a business rules engine powered by Symbolic AI, processing millions of decisions daily. - **[jBPM](https://kie.apache.org/)** – a flexible workflow engine for automating complex business processes. - **[OptaPlanner](https://kie.apache.org/)** – an AI-driven constraint solver for optimization challenges. - **[Kogito](https://kogito.kie.org/)** – the cloud-native evolution designed for event-driven automation. - **[SonataFlow](https://sonataflow.org/)** – a workflow engine for orchestration and choreography of cloud services. Together, these projects form the foundation of enterprise automation across finance, healthcare, and government sectors. ## The Apache Transition: A Strategic Evolution For years, KIE technologies were the backbone of Red Hat Process Automation Manager (RHPAM) and Red Hat Decision Manager (RHDM). Their move to the Apache Software Foundation marks a milestone of open source maturity — ensuring vendor neutrality and transparent community governance. As documented in the [Apache KIE proposal](https://cwiki.apache.org/confluence/display/INCUBATOR/KIE%2BProposal) by Mark Proctor and Alex Porcelli, this transition separates community innovation from commercial delivery. The community drives open development, while enterprise vendors provide hardened, supported distributions — preserving accessibility and accelerating progress free from proprietary constraints. ## Aletyx & Apache KIE: Bridging Open Source and Enterprise Needs Aletyx plays a dual role: we contribute upstream while delivering enterprise-grade builds downstream. Our engineers actively maintain Drools, Kogito, and related projects, improving stability, performance, and documentation. We also maintain free public tools such as: - [playground.aletyx.ai](https://playground.aletyx.ai/) - [start.aletyx.ai](https://start.aletyx.ai/) - [vscode.aletyx.ai](https://marketplace.visualstudio.com/publishers/Aletyx) Becoming an official vendor validates our mission to connect open innovation with enterprise reliability — where: - Open source drives new ideas - Vendors deliver production-ready solutions - Collaboration strengthens standards, quality, and security ## Aletyx Enterprise Offerings Our portfolio goes beyond packaging open source. We deliver Decision Intelligence and Automation Intelligence solutions for scalable orchestration and AI-enabled decisioning. Decision Control empowers business users to model logic with DMN, without coding. The [Aletyx Build of Drools](https://aletyx.ai/enterprise-drools/) offers an enhanced distribution with native Agentic and GenAI integration via the built-in [MCP protocol](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) — simplifying upgrades and eliminating technical barriers seen elsewhere. For orchestration, the [Aletyx Build of Kogito](https://aletyx.ai/intelligent-process-automation/) handles scalability for complex processes while integrating seamlessly with our decision stack. Beyond technology, we’ve simplified enterprise economics. Our [transparent, predictable pricing](https://aletyx.ai/pricing/) removes core counting and usage-based costs, offering unlimited deployment at a flat rate. ## Sustainable Innovation Community innovation fuels progress; enterprise rigor ensures quality, security, and continuity. Together they create a sustainable model for intelligent automation. Aletyx transforms upstream advancements into production-ready solutions with [migration paths](https://aletyx.ai/modernization/), direct engineering support, and flat-rate pricing. Our [training](https://aletyx.ai/training/) and [consulting](https://aletyx.ai/consulting/) offerings help organizations modernize and adopt hybrid AI architectures that combine rules, processes, and GenAI safely. ## Looking Ahead With Apache KIE’s recent 10.1.0 milestone, Aletyx remains committed to advancing both the technology and its global adoption. We continue expanding partnerships, contributing to core development, and enabling enterprises to modernize with confidence on an open, future-ready foundation. --- **Resources:** - View our listing in [Apache KIE Commercial Support Page](https://kie.apache.org/docs/community/commercial-support/) - Try the Aletyx Playground: [playground.aletyx.ai](https://playground.aletyx.ai/) - Easily kickstart new projects using: [start.aletyx.ai](https://start.aletyx.ai/) - Aletyx Design for VS Code: [vscode.aletyx.ai](https://marketplace.visualstudio.com/publishers/Aletyx) - Documentation: [docs.aletyx.ai](https://aletyx.ai/docs) Aletyx stands as a trusted vendor and steadfast contributor, advancing the mission to make enterprise automation accessible, extensible, and resilient for everyone. ## References 1. [Commercial Support for Apache KIE](https://kie.apache.org/docs/community/commercial-support/) — Apache KIE ## About the author [Alex Porcelli](https://aletyx.ai/authors/alex-porcelli/) Co-founder & CEO Nearly two decades building Drools, jBPM, and Kogito as part of the product teams at Red Hat and IBM. Apache KIE PPMC member, now building accountable automation for the age of AI. [More from Alex](https://aletyx.ai/authors/alex-porcelli/) --- # Aletyx Announces Strategic Partnership with Indo-Sakura and UMEZO in Japan Source: https://aletyx.ai/news/aletyx-partnership-with-indo-sakura-and-umezo-in-japan/ [Partnerships](https://aletyx.ai/topics/partnerships/) [Apache KIE](https://aletyx.ai/topics/apache-kie/) [Kogito](https://aletyx.ai/topics/kogito/) September 15, 2025 3 min ![Two people shaking hands in front of a business chart](https://aletyx.ai/_astro/partnership.C8t5cXZX_NmI0I.webp) Published September 15, 2025 We are proud to announce a strategic partnership between Aletyx, Indo-Sakura Software Japan K.K. (Indo-Sakura), and UMEZO Consulting LLC (UMEZO) to bring decision intelligence automation to the Japanese enterprise market. Through this collaboration, Indo-Sakura and UMEZO will work closely with Aletyx, providing Japanese organizations direct access to Aletyx enterprise builds of Drools and Kogito. Japan now unlocks local help to the best version of these automation technologies, with long-term support, predictable pricing, and exclusive AI innovation such as, native integration with agentic AI through the Model Context Protocol (MCP). Our partners can simplify your access to a roadmap of automation solutions fully focused on enabling hybrid AI systems. Indo-Sakura brings over two decades of expertise and experience, a strong vision for modernization, and a clear commitment to delivering high-quality enterprise platforms to the region. UMEZO contributes deep expertise in the decision intelligence and modernization space. Together, they form a powerful alliance to support organizations in Japan as they modernize core decision systems and embrace new AI-enabled architectures. > “This partnership with Aletyx and UMEZO is a natural extension of our two-decade journey in building reliable enterprise platforms. We’re excited to bring Japan closer to the future of intelligent automation and agentic AI. Together, we’re enabling organizations to modernize with confidence and clarity.” — Atul Paswan, CEO, Indo-Sakura What makes this partnership especially meaningful is our shared history. Executives at both Indo-Sakura and UMEZO have long-standing roots in Apache KIE technologies, having worked closely with Drools and jBPM for many years. This is not just a business alignment, it is a continuation of a journey that began over a decade ago with a common goal: building trustworthy, scalable, enterprise-grade modern platforms. > “Logic is the brain of any application—an essential component that drives its intelligence and behavior. Aletyx, a leading open-source provider at the forefront of Symbolic AI, sits at the heart of this emerging field. We are thrilled to announce the partnership between Aletyx and Indo-Sakura, and we look forward to delivering even greater value to our clients through this exciting collaboration.” — Masahiko Umeno, CEO, UMEZO At Aletyx, we are thrilled to work closely with these respected partners, combining deep local market knowledge with modern enterprise technology. Together, we will help Japanese organizations reduce risk, accelerate innovation, and drive meaningful modernization and transformation through explainable, future-ready systems built for scale. > “Aletyx is excited to work together again with the best of the best in the region. It’s not just their market knowledge, but their deep understanding of customer needs that, combined with Aletyx technologies, will help create meaningful change in the local market.” — Alex Porcelli, Co-founder, Aletyx For more information about how this partnership can support your decision automation initiatives in Japan, please reach out to us: **Aletyx** 📧 [contact@aletyx.com](mailto:contact@aletyx.com) 🌐 [aletyx.ai](https://aletyx.ai/) **Indo-Sakura Software Japan K.K.** 📧 [info.japan@indosakura.com](mailto:info.japan@indosakura.com) 🌐 [www.indosakura.com](https://www.indosakura.com/) **UMEZO** 📧 [contact@UMEZO.jp](mailto:contact@UMEZO.jp) 🌐 [UMEZO.jp](https://www.umezo.jp/) --- # Announcing Strategic Partnership with NVS Consulting: Accelerating Enterprise Innovation in North America Source: https://aletyx.ai/news/announcing-nvs-aletyx-strategic-partnership/ [Partnerships](https://aletyx.ai/topics/partnerships/) [Artificial Intelligence](https://aletyx.ai/topics/artificial-intelligence/) [Process Automation](https://aletyx.ai/topics/process-automation/) July 17, 2025 1 min ![Two people shaking hands in front of a business chart](https://aletyx.ai/_astro/partnership.C8t5cXZX_NmI0I.webp) Published July 17, 2025 Today we announce a strategic partnership between Aletyx and NVS Consulting. This alliance empowers enterprises across North America through their modernization challenges and objectives involving: ## Partnership Focus Areas - **Scalable and decision intelligence automation** - Streamlining complex business processes with AI-driven decision-making capabilities - **Agentic AI** - Implementing autonomous AI systems that can act independently to achieve business objectives - **Modernization for automation on hybrid-clouds** - Enabling seamless integration across cloud and on-premises environments ## Strategic Alliance Benefits The partnership aims to help enterprises navigate complex digital transformation challenges by combining Aletyx’s technological capabilities with NVS Consulting’s strategic expertise. This collaboration will enable organizations to: - Accelerate their AI adoption journey - Implement robust automation solutions - Navigate hybrid-cloud modernization initiatives - Leverage cutting-edge decision automation technologies ## About the Partnership By joining forces, Aletyx and NVS Consulting are positioning themselves to deliver comprehensive solutions that address the full spectrum of enterprise modernization needs across North America. --- *For more information about this partnership and how it can benefit your organization, [contact our team](https://aletyx.ai/contact/).* --- # DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence Source: https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/ [Events & Community](https://aletyx.ai/topics/events-and-community/) [DMN](https://aletyx.ai/topics/dmn/) [Drools](https://aletyx.ai/topics/drools/) September 15, 2025 2 min ![Warm orange and blue lights in a conference venue](https://aletyx.ai/_astro/event-hero.BKDNyS92_2jk063.webp) Published September 15, 2025 [Aletyx sponsors DecisionCAMP 2025](https://decisioncamp2025.wordpress.com/vendor-news/), the leading conference for decision intelligence, automation and business rules management, taking place September 22–24, 2025. This premier event brings together decision practitioners, DMN experts, and developers to learn, share experiences, and advance enterprise decision‑making technologies. ## DecisionCAMP 2025: The Premier Decision Intelligence Conference DecisionCAMP has been the premier gathering for decision intelligence practitioners since 2008. It brings together experts who are pushing the boundaries of business rules, machine learning, optimization, and decision automation technologies. For nearly two decades, this event has delivered actionable insights from decision management experts through in‑depth technical sessions. DecisionCAMP’s mission aligns perfectly with ours: helping organizations build and maintain intelligent decision services that drive real business value. ## Our Commitment to Decision Intelligence At Aletyx, we drive community growth in a sustainable way: as we nurture the Apache KIE community and evolve its technologies, in parallel we also craft enterprise solutions — [Aletyx build of Drools](https://aletyx.ai/enterprise-drools/) and [Aletyx build of Kogito](https://aletyx.ai/intelligent-process-automation/) — where we carefully craft enterprise‑grade intelligent decisioning and process automation. Our sponsorship of [DecisionCAMP](https://decisioncamp2025.wordpress.com/) reflects our deep commitment to advancing the standards and practices that power enterprise‑grade decision automation. We’re not just observers in this space. We bring core contributor‑level expertise in rule technologies, having helped build the very foundations that many decision automation platforms rely on today. ## Community Support: The Future of Decision Intelligence DecisionCAMP 2025 is where practitioners, architects, and decision‑makers will gather and shape the future of how businesses automate complex decisions. As a strong supporter of communities, and with our strong dedication to the field of decision intelligence, we are proud to support, participate and fuel AI‑driven innovation and enterprise adoption of modern software solutions. ## Join Us at DecisionCAMP 2025 Whether you’re working with DMN, exploring decision automation platforms, or building AI‑enhanced business rules, DecisionCAMP offers unparalleled opportunities to learn from industry leaders and connect with fellow practitioners. We’ll be there to discuss the latest in decision intelligence technologies and share insights from our work with enterprise automation challenges. **Talk highlight:** [Turning Decisions into Agents: DMN Meets GenAI, by Alex Porcelli](https://decisioncamp2025.wordpress.com/program/#AlexPorcelli) DecisionCAMP 2025 (Virtual), Sep 23rd, 11:00 EDT Save the date, and see you at DecisionCAMP! --- Learn more about DecisionCAMP 2025: [https://decisioncamp2025.wordpress.com](https://decisioncamp2025.wordpress.com/) To stay tuned about Aletyx exciting updates and other events, follow us on [LinkedIn](https://www.linkedin.com/company/aletyx) and [Twitter/X](https://x.com/aletyxai)! ## References 1. [Aletyx Sponsors DecisionCAMP 2025](https://decisioncamp2025.wordpress.com/vendor-news/) — DecisionCAMP --- # Aletyx Origin Source: https://aletyx.ai/origin/ Enterprise support for RHDM, BRMS, and Drools Still running RHDM, Red Hat BRMS, or older Drools in production? Origin is the supported enterprise build of the software you already deploy. Full v7 backward compatibility. Active CVE patches. Engineer-led support. No rewrite required. [Subscribe now](https://aletyx.ai/origin/#pricing) [Talk to us](https://aletyx.ai/origin/#origin-contact) v7 backward compatibility Engineer-led support Active CVE patches ## Origin was built for teams like yours If any of the following sound familiar, Origin is the right fit. - Running RHDM, Red Hat BRMS, or Drools 6, 7, or 8 in production - Previous vendor can no longer support your version - New vendor forces a full rewrite - Workload fits in up to 8 cores ## What You Get ### Stay secure. CVE patches and remediation guidance delivered to your team. Apply them inside your environment without hunting for fixes or running exposed. ### Stay running. Full v7 backward compatibility. Your existing rules, decisions, and integrations continue to work. ### Real engineers. Direct access to people who have spent years inside this engine. No scripted first-line. ### Right-sized. Subscription sized for up to 8 production CPU cores. Unlimited dev, test, and staging environments at no extra cost. ## Decades inside this engine Our engineers have spent their careers working with this technology. Engine internals. Compiler behavior. Production troubleshooting across enterprises around the world. When you open a ticket, you talk to people who have seen every corner of the code from the inside. ## Same operating model. Modern foundation. Origin is the supported enterprise build of the software you already run. You download, deploy, and operate inside your own infrastructure. No platform to adopt. No architectural change. What you get is a hardened, modern foundation, backed by engineer-led support and active CVE patches. ![UMEZO Consulting](https://aletyx.ai/_astro/umezo-mark.CE7KsJz8_Z1u6HjF.webp) ## Specialized migration support in Japan For customers in Japan, we partner with UMEZO Consulting LLC, a highly specialized firm that handles every aspect of the migration from RHDM, Red Hat BRMS, or Drools to Aletyx. Assessment, architecture review, rules modernization, testing, cutover. Together we deliver the product and the hands-on expertise to get you to production safely. [Contact UMEZO Consulting](https://aletyx.ai/origin/#origin-contact) ## Simple pricing Less than the cost of one failed deployment or weeks debugging an unsupported system. Monthly Yearly ### Origin --- $20,000/ year paid annually by invoice --- - Up to 8 production CPU cores - Unlimited dev and test environments - Validated compatibility and CVE management - Engineer-led support - Full v7 backward compatibility [Subscribe now](https://buy.stripe.com/cNibJ31WgaLgadmeMA5c402) [Ask about annual invoicing](https://aletyx.ai/origin/#origin-contact) FAQ ## Questions we hear often 01 Do I need to rewrite my rules? No. Full v7 backward compatibility means your existing rules, decisions, and integrations continue to work. 02 How does Origin get deployed? You deploy it in your own infrastructure, the same way you deploy RHDM, Red Hat BRMS, or Drools today. No platform to adopt, no architectural change required. 03 My system integrator built the original deployment. What about them? Keep working with them, or engage UMEZO Consulting directly. Either way, Origin provides the supported product underneath. 04 Can I pay by annual invoice? Yes. $20,000/year prepaid, processed through your procurement channel. 05 What if my workload exceeds 8 cores? Aletyx Horizon or Innovator may be a better fit. We can help you evaluate the right option. 06 Is Aletyx affiliated with Red Hat or IBM? No. Aletyx is an independent company. Red Hat Decision Manager, Red Hat BRMS, Drools, and related names are trademarks of their respective owners. ## Ready to move forward? ### Subscribe online. Deployment guidance included. [Subscribe now](https://buy.stripe.com/cNibJ31WgaLgadmeMA5c402) ## Reach out in Japan Joint Aletyx and UMEZO Consulting team. --- # Stop paying the "success tax" on your automation Source: https://aletyx.ai/pricing/ Predictable, transparent, flat-fee Legacy vendors penalize you for scaling. We don't. One flat fee covers your environment. Spin up as many pods, containers, and vCPUs as you need. No audits. No surprises. [Get a Quote](https://aletyx.ai/contact/?interest=yes) [Compare to legacy pricing](https://aletyx.ai/pricing/#comparison) ## We license the value, not the CPU In a Cloud-Native world, counting cores is obsolete. Why should your license cost double just because you added nodes to handle a Black Friday spike? Aletyx prices on capability, not infrastructure. You pay for the depth of governance and support your teams need, not the cores they happen to run on. ### Launch new projects Pay the same. ### Handle demand spikes Pay the same. ### Decompose the monolith Pay the same. Ready for real production environments ## Built for systems that must perform reliably under audit and at scale Aletyx is designed for long-term production use in regulated, high-volume environments. Decision Intelligence Intelligent Process Automation ### Pioneer For startups, SMBs, and nonprofits with light workloads and core features. --- $25k/Year --- - Support: Business Hours - Support Access: 5 - Support Scope: Production - Recurring security scans - Hosted Maven Repository - Core features [Start with Pioneer](https://aletyx.ai/contact/?interest=yes) Recommended ### Innovator For teams innovating with decisions, AI guardrails, and full support. --- $50k/Year --- - Everything in Pioneer - Support: Business Hours - Support Access: 5 - Vulnerability report - Support Scope: Development and Production - Ready for agentic AI (MCP) [Start innovating](https://aletyx.ai/contact/?interest=yes) ### Horizon For enterprises needing performance, migration, and premium support. --- $100k/Year --- - Everything in Innovator + - Support: 24×7 - Support Access: 10 - Channels: Email, Ticket, Phone - Classic RuleFlow support - Enhanced onboarding and migration assistance [Start with Horizon](https://aletyx.ai/contact/?interest=yes) ### Keystone For organizations deploying across multiple entities, subsidiaries, or affiliates. --- Custom --- - Everything in Horizon + - Support: 24×7 - Support Access: Unlimited - Priority bug fixes and RFEs - Quarterly Architecture review - (1) Virtual Training [Request a Quote](https://aletyx.ai/contact) The "vs. legacy" comparison ## The "hidden costs" of legacy vs.the clarity of Aletyx Cost Driver Legacy Vendor (IBM/Red Hat) Aletyx Scaling **The "Success Tax":** Costs rise linearly with every vCPU you add. **Flat Fee:** Scale horizontally without penalty. Architecture **Monolith-First:** Penalizes microservices with high per-core counts. **Cloud-Native First:** Encourages distributed architectures. Audits **Aggressive:** Teams live in fear of non-compliance fines. **Zero transactional audits:** Simple, trust-based licensing model. Environments Often chargeable or limited. Separate rules for disaster recovery. **All included:** Every environment covered under one subscription. No distinctions, no separate licenses for disaster recovery. Cost Driver ### Scaling Aletyx **Flat Fee:** Scale horizontally without penalty. Legacy Vendor (IBM/Red Hat) **The "Success Tax":** Costs rise linearly with every vCPU you add. Cost Driver ### Architecture Aletyx **Cloud-Native First:** Encourages distributed architectures. Legacy Vendor (IBM/Red Hat) **Monolith-First:** Penalizes microservices with high per-core counts. Cost Driver ### Audits Aletyx **Zero transactional audits:** Simple, trust-based licensing model. Legacy Vendor (IBM/Red Hat) **Aggressive:** Teams live in fear of non-compliance fines. Cost Driver ### Environments Aletyx **All included:** Every environment covered under one subscription. No distinctions, no separate licenses for disaster recovery. Legacy Vendor (IBM/Red Hat) Often chargeable or limited. Separate rules for disaster recovery. Frequently asked questions ## Answers to your CFO's questions [View plans](https://aletyx.ai/pricing/#pricing-cards) 01 Do you really mean "Unlimited" cores? Yes. Our flat-fee tiers have no per-core or per-CPU metering. Deploy across as many cores, containers, or nodes as your architecture requires—your subscription price stays the same regardless of infrastructure scale. 02 What's included in non-production environments? All tiers include unlimited use in development, testing, and staging environments at no additional cost. Only production deployments count toward your subscription. 03 Can I upgrade from Pioneer to Horizon later? Absolutely. You can upgrade tiers at any time. We'll prorate the difference for the remainder of your annual term, so you only pay the delta when you're ready to scale. 04 How does the "Keystone" multi-entity model work? Keystone is designed for organizations deploying Aletyx across multiple business units, subsidiaries, or affiliates under a single agreement. It includes a dedicated Customer Success Manager, priority engineering access, and custom terms tailored to enterprise-wide rollouts. Lock in your rate ## Predictable outcomes.Predictable costs Stop budgeting for "unexpected overages." Lock in your modernization cost today. [Get a Custom Quote](https://aletyx.ai/contact/?interest=yes) Response within 24 hours. No obligation. --- # Free, open, and built for the community Source: https://aletyx.ai/tools-for-community/ Welcome to the Aletyx experience Model decisions and workflows, monitor Apache KIE vulnerabilities, and explore our developer tools without installing anything. Everything here is free for the open source community. Free CVE monitoring for the open source community ## Free CVE monitoring for the open source community Keeping open source secure shouldn’t require an enterprise contract. That’s why Aletyx provides free, public CVE monitoring for the open-source components that power Drools and Kogito. Through kiecve.aletyx.ai, the community can track known vulnerabilities, versions affected, severity levels, and remediation timelines — all in one place, continuously updated. [Start Guided Pilot](https://aletyx.ai/free-trial/) ![Vulnerability Dashboard showing CVE summary and severity distribution](https://aletyx.ai/_astro/cve-dashboard.CLTIn9A1_Z2tOnF8.webp) ## Explore, prototype & accelerate Playground lets you dive right into modeling decisions (DMN) and workflows (BPMN)—without installing anything. It’s a live, hosted tool that gives you full authoring power, including an interactive DMN runner. And when you’re ready to move forward, Aletyx Playground becomes your launchpad: with just one click, apply the Aletyx Accelerator and get a fully-functional, best-practice project ready to run. Whether you’re experimenting or building fast, this is where the Aletyx journey begins. [Start Guided Pilot](https://aletyx.ai/free-trial/) ![Aletyx Playground interface for modeling decisions and workflows](https://aletyx.ai/_astro/playground.tyz-hBQi_Z1bSt0t.webp) VS Code Extension ## Build anywhere—without the setup struggles Use the Aletyx VS Code extension to edit DMN and BPMN models directly in your IDE. Add our hosted Maven repository—and you’re ready to compile in seconds. Pull runtime images from our container registry to deploy faster. [Start Guided Pilot](https://aletyx.ai/free-trial/) ![Aletyx VS Code extension for editing DMN and BPMN models](https://aletyx.ai/_astro/vscode.DlOa45zn_Z1FQeca.webp) ## Your always‑on guide—built‑in docs for every role Get answers when you need them. Aletyx documentation is built to serve everyone: developers, business users, architects, and newcomers alike. Organized, searchable, and continuously updated. And if we’re missing something? Just tell us—we’ll evaluate and update the docs promptly. [Start Guided Pilot](https://aletyx.ai/free-trial/) ![Aletyx documentation interface](https://aletyx.ai/_astro/docs.BrohfyEd_Z1g7g6b.webp) ## More than technology,an open experience From live playgrounds to curated documentation and editor plugins, Aletyx delivers a complete experience to the open source community. We believe in transparency, simplicity, and access. That’s why we offer clear pricing and open tools. Explore more at [aletyx.ai/pricing](https://aletyx.ai/pricing/), or subscribe to our newsletter to stay in the loop. Let’s build the future of automation—together. Your last chance ## Solve the “unsolvable” problem If your current partners are stuck, it’s time to call the creators. [Contact Engineering Sales](https://aletyx.ai/contact/) Direct discussion with a technical lead, not a sales rep. --- # Apache KIE Source: https://aletyx.ai/topics/apache-kie/ Topic News and technical guidance about the Apache KIE ecosystem and its enterprise use. ## [Announcing Aletyx Decision Control Sandbox on AWS Marketplace](https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/) The fastest and simplest path to decision intelligence. In a few minutes, a fully automated provisioning prepares everything you need to get started with Decision Control Sandbox on AWS. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx Officially Listed as Vendor of Apache KIE](https://aletyx.ai/news/aletyx-official-apache-kie-vendor/) Aletyx is thrilled to announce our official listing as a vendor on the Apache KIE commercial support page, underscoring our commitment to the open source ecosystem and enterprise community. Topics: Apache KIE, Drools. Reading time: 3 min ## [Aletyx Announces Strategic Partnership with Indo-Sakura and UMEZO in Japan](https://aletyx.ai/news/aletyx-partnership-with-indo-sakura-and-umezo-in-japan/) Announcing our strategic partnership with Indo-Sakura Software Japan K.K. (Indo-Sakura), and UMEZO Consulting LLC (UMEZO). Topics: Partnerships, Apache KIE. Reading time: 3 min ## [Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation](https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/) Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Enabling Teams with Apache KIE 10: Aletyx's Workshop on Kogito-based Workflows](https://aletyx.ai/case-studies/aletyx-workshop-kogito/) Aletyx recently delivered an Apache KIE 10 Workshop to a science and technology customer, providing hands-on training in Kogito workflows, decision modeling, and production-ready practices. Topics: Enterprise Enablement, Apache KIE. Reading time: 2 min ## [The Missing Manual for Kogito: How to Use Java APIs Instead of Auto-Generated REST Endpoints](https://aletyx.ai/blog/how-to-use-java-apis-with-kogito-process/) Learn how to trigger Kogito BPMN processes using the Java API—without relying on auto-generated REST endpoints. Topics: Enterprise Enablement, Apache KIE. Reading time: 3 min --- # Artificial Intelligence Source: https://aletyx.ai/topics/artificial-intelligence/ Topic Enterprise AI architecture, implementation, reliability, and operational guidance. ## [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min ## [The Gap Between Policy and the Model](https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/) Decision analysts understand policy changes first, but often can't ship them to production. Learn how Aletyx Decision Control and the Aletyx AI Assistant close the gap between business intent and working decision models. Topics: AI Assistant, Artificial Intelligence. Reading time: 6 min ## [Announcing Aletyx Decision Control Sandbox on AWS Marketplace](https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/) The fastest and simplest path to decision intelligence. In a few minutes, a fully automated provisioning prepares everything you need to get started with Decision Control Sandbox on AWS. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Announcing Strategic Partnership with NVS Consulting: Accelerating Enterprise Innovation in North America](https://aletyx.ai/news/announcing-nvs-aletyx-strategic-partnership/) Today we announce a strategic partnership between Aletyx and NVS Consulting, combining technological capabilities with strategic expertise to help enterprises navigate complex digital transformation challenges. Topics: Partnerships, Artificial Intelligence. Reading time: 1 min ## [Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation](https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/) Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025](https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/) At Arc of AI 2025, Aletyx co-founder Alex Porcelli shared groundbreaking insights on combining Large Language Models with Rule Engines to create more controlled and reliable AI systems. Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI](https://aletyx.ai/events/aletyx-at-decisioncamp-2025/) Join Aletyx at DecisionCAMP 2025 to learn how to solve GenAI's reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Essential Concepts for Navigating Enterprise AI Trends](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/) Cut through the noise and buzzwords and understand the foundational concepts associated with AI, their applications, and the trade-offs enterprises must consider. Topics: Artificial Intelligence, Model Context Protocol. Reading time: 8 min ## [Overcoming Challenges: Enterprise Path to Intelligent Solutions](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/) Why are intelligent systems often associated with lack of compliance? Unpack the trade-offs derived from the characteristics of the types. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 4 min ## [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/) While LLMs capture headlines, enterprise AI success requires a broader architectural approach. Discover how to build intelligent systems that combine multiple AI paradigms for real-world business applications. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 5 min ## [Automatic DMN to LLM Integration with MCP: Exclusive Aletyx Feature for Enterprise AI](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) Bringing AI into your enterprise is no longer just about innovation—it’s about control, safety, and scale. Topics: Model Context Protocol, DMN. Reading time: 2 min --- # Decision Intelligence Source: https://aletyx.ai/topics/decision-intelligence/ Topic Methods and platforms for making business decisions explicit, testable, explainable, and reusable. ## [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min ## [Decision Tables: What They Look Like for Business Users](https://aletyx.ai/blog/decision-tables-for-business-users/) Decision tables make business policies visible, testable, and changeable without code. See what they look like when business people use them, and how AI accelerates authoring. Topics: Decision Intelligence, DMN. Reading time: 6 min ## [The Gap Between Policy and the Model](https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/) Decision analysts understand policy changes first, but often can't ship them to production. Learn how Aletyx Decision Control and the Aletyx AI Assistant close the gap between business intent and working decision models. Topics: AI Assistant, Artificial Intelligence. Reading time: 6 min ## [Announcing Aletyx Decision Control Sandbox on AWS Marketplace](https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/) The fastest and simplest path to decision intelligence. In a few minutes, a fully automated provisioning prepares everything you need to get started with Decision Control Sandbox on AWS. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx and Athena Decision Systems Announce Strategic Partnership](https://aletyx.ai/news/aletyx-and-athena-decision-systems-announce-strategic-partnership/) Aletyx announces strategic partnership with Athena Decision Systems, bringing enterprise builds of Drools and Kogito to European customers with expert implementation support. Topics: Partnerships, Decision Intelligence. Reading time: 2 min ## [Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025](https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/) At Arc of AI 2025, Aletyx co-founder Alex Porcelli shared groundbreaking insights on combining Large Language Models with Rule Engines to create more controlled and reliable AI systems. Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Essential Concepts for Navigating Enterprise AI Trends](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/) Cut through the noise and buzzwords and understand the foundational concepts associated with AI, their applications, and the trade-offs enterprises must consider. Topics: Artificial Intelligence, Model Context Protocol. Reading time: 8 min ## [Overcoming Challenges: Enterprise Path to Intelligent Solutions](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/) Why are intelligent systems often associated with lack of compliance? Unpack the trade-offs derived from the characteristics of the types. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 4 min ## [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/) While LLMs capture headlines, enterprise AI success requires a broader architectural approach. Discover how to build intelligent systems that combine multiple AI paradigms for real-world business applications. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 5 min --- # DMN Source: https://aletyx.ai/topics/dmn/ Topic Decision Model and Notation guidance, examples, integrations, and community updates. ## [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min ## [Decision Tables: What They Look Like for Business Users](https://aletyx.ai/blog/decision-tables-for-business-users/) Decision tables make business policies visible, testable, and changeable without code. See what they look like when business people use them, and how AI accelerates authoring. Topics: Decision Intelligence, DMN. Reading time: 6 min ## [The Gap Between Policy and the Model](https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/) Decision analysts understand policy changes first, but often can't ship them to production. Learn how Aletyx Decision Control and the Aletyx AI Assistant close the gap between business intent and working decision models. Topics: AI Assistant, Artificial Intelligence. Reading time: 6 min ## [Announcing Aletyx Decision Control Sandbox on AWS Marketplace](https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/) The fastest and simplest path to decision intelligence. In a few minutes, a fully automated provisioning prepares everything you need to get started with Decision Control Sandbox on AWS. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence](https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/) Aletyx sponsors DecisionCAMP 2025, Sep 22–24. Join us for cutting‑edge sessions on DMN, business rules, and enterprise decision automation. Topics: Events & Community, DMN. Reading time: 2 min ## [Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025](https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/) At Arc of AI 2025, Aletyx co-founder Alex Porcelli shared groundbreaking insights on combining Large Language Models with Rule Engines to create more controlled and reliable AI systems. Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI](https://aletyx.ai/events/aletyx-at-decisioncamp-2025/) Join Aletyx at DecisionCAMP 2025 to learn how to solve GenAI's reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/) While LLMs capture headlines, enterprise AI success requires a broader architectural approach. Discover how to build intelligent systems that combine multiple AI paradigms for real-world business applications. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 5 min ## [Automatic DMN to LLM Integration with MCP: Exclusive Aletyx Feature for Enterprise AI](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) Bringing AI into your enterprise is no longer just about innovation—it’s about control, safety, and scale. Topics: Model Context Protocol, DMN. Reading time: 2 min --- # Drools Source: https://aletyx.ai/topics/drools/ Topic Technical perspectives and news about Drools rules and decision automation. ## [Aletyx Officially Listed as Vendor of Apache KIE](https://aletyx.ai/news/aletyx-official-apache-kie-vendor/) Aletyx is thrilled to announce our official listing as a vendor on the Apache KIE commercial support page, underscoring our commitment to the open source ecosystem and enterprise community. Topics: Apache KIE, Drools. Reading time: 3 min ## [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence](https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/) Aletyx sponsors DecisionCAMP 2025, Sep 22–24. Join us for cutting‑edge sessions on DMN, business rules, and enterprise decision automation. Topics: Events & Community, DMN. Reading time: 2 min ## [Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation](https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/) Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI](https://aletyx.ai/events/aletyx-at-decisioncamp-2025/) Join Aletyx at DecisionCAMP 2025 to learn how to solve GenAI's reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Architecting Intelligence Beyond LLMs](https://aletyx.ai/blog/architecting-intelligence-beyond-llms/) While LLMs capture headlines, enterprise AI success requires a broader architectural approach. Discover how to build intelligent systems that combine multiple AI paradigms for real-world business applications. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 5 min ## [Automatic DMN to LLM Integration with MCP: Exclusive Aletyx Feature for Enterprise AI](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) Bringing AI into your enterprise is no longer just about innovation—it’s about control, safety, and scale. Topics: Model Context Protocol, DMN. Reading time: 2 min --- # Events & Community Source: https://aletyx.ai/topics/events-and-community/ Topic Conference sessions, talks, sponsorships, and contributions to the decision automation community. ## [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [DecisionCAMP 2025: Announcing Aletyx Sponsorship and Influence on Enterprise Intelligence](https://aletyx.ai/news/decisioncamp-2025-announcing-aletyx-sponsorship-and-influence-on-enterprise-intelligence/) Aletyx sponsors DecisionCAMP 2025, Sep 22–24. Join us for cutting‑edge sessions on DMN, business rules, and enterprise decision automation. Topics: Events & Community, DMN. Reading time: 2 min ## [Taming LLMs with Rule Engines: Aletyx Co-Founder Alex Porcelli's Insights at Arc of AI 2025](https://aletyx.ai/events/taming-llms-with-rule-engines-aletyx-co-founder-alex-porcellis-insights-at-arc-of-ai-2025/) At Arc of AI 2025, Aletyx co-founder Alex Porcelli shared groundbreaking insights on combining Large Language Models with Rule Engines to create more controlled and reliable AI systems. Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI](https://aletyx.ai/events/aletyx-at-decisioncamp-2025/) Join Aletyx at DecisionCAMP 2025 to learn how to solve GenAI's reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min --- # Governance & Compliance Source: https://aletyx.ai/topics/governance-and-compliance/ Topic Approaches for building accountable, auditable, and policy-aligned AI and decision systems. ## [Meeting the 2026 GSE Governance Rules with Accountable AI](https://aletyx.ai/blog/2026-mortgage-gse-compliance/) How Aletyx helps you build AI applications that are accountable for regulatory compliance, including the 2026 GSE AI governance requirements. Topics: Governance & Compliance, Artificial Intelligence. Reading time: 11 min ## [Decision Tables: What They Look Like for Business Users](https://aletyx.ai/blog/decision-tables-for-business-users/) Decision tables make business policies visible, testable, and changeable without code. See what they look like when business people use them, and how AI accelerates authoring. Topics: Decision Intelligence, DMN. Reading time: 6 min ## [The Gap Between Policy and the Model](https://aletyx.ai/blog/aletyx-ai-assistant-dmn-decision-models/) Decision analysts understand policy changes first, but often can't ship them to production. Learn how Aletyx Decision Control and the Aletyx AI Assistant close the gap between business intent and working decision models. Topics: AI Assistant, Artificial Intelligence. Reading time: 6 min ## [Overcoming Challenges: Enterprise Path to Intelligent Solutions](https://aletyx.ai/blog/overcoming-challenges-enterprise-path-to-intelligent-solutions/) Why are intelligent systems often associated with lack of compliance? Unpack the trade-offs derived from the characteristics of the types. Topics: Artificial Intelligence, Decision Intelligence. Reading time: 4 min --- # Kogito Source: https://aletyx.ai/topics/kogito/ Topic Kogito workflow architecture, Java APIs, enterprise builds, and implementation guidance. ## [Aletyx Officially Listed as Vendor of Apache KIE](https://aletyx.ai/news/aletyx-official-apache-kie-vendor/) Aletyx is thrilled to announce our official listing as a vendor on the Apache KIE commercial support page, underscoring our commitment to the open source ecosystem and enterprise community. Topics: Apache KIE, Drools. Reading time: 3 min ## [Aletyx Announces Strategic Partnership with Indo-Sakura and UMEZO in Japan](https://aletyx.ai/news/aletyx-partnership-with-indo-sakura-and-umezo-in-japan/) Announcing our strategic partnership with Indo-Sakura Software Japan K.K. (Indo-Sakura), and UMEZO Consulting LLC (UMEZO). Topics: Partnerships, Apache KIE. Reading time: 3 min ## [Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation](https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/) Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Enabling Teams with Apache KIE 10: Aletyx's Workshop on Kogito-based Workflows](https://aletyx.ai/case-studies/aletyx-workshop-kogito/) Aletyx recently delivered an Apache KIE 10 Workshop to a science and technology customer, providing hands-on training in Kogito workflows, decision modeling, and production-ready practices. Topics: Enterprise Enablement, Apache KIE. Reading time: 2 min ## [The Missing Manual for Kogito: How to Use Java APIs Instead of Auto-Generated REST Endpoints](https://aletyx.ai/blog/how-to-use-java-apis-with-kogito-process/) Learn how to trigger Kogito BPMN processes using the Java API—without relying on auto-generated REST endpoints. Topics: Enterprise Enablement, Apache KIE. Reading time: 3 min --- # Model Context Protocol Source: https://aletyx.ai/topics/model-context-protocol/ Topic Using MCP to connect AI assistants with governed decisions, rules, and enterprise workflows. ## [Announcing Aletyx Decision Control Sandbox on AWS Marketplace](https://aletyx.ai/news/aletyx-decision-control-sandbox-live-on-aws/) The fastest and simplest path to decision intelligence. In a few minutes, a fully automated provisioning prepares everything you need to get started with Decision Control Sandbox on AWS. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Aletyx at AI\_dev Europe 2025: Decision Intelligence with GenAI, Drools and DMN](https://aletyx.ai/events/aletyx-at-ai_dev-2025/) Dive into our session at Amsterdam’s top open-source GenAI summit, where we’ll unpack real-world strategies for blending LLMs with Drools and DMN to build compliant, explainable AI systems that drive Topics: Events & Community, Artificial Intelligence. Reading time: 2 min ## [Watch: Architecting the AI Bridge with LLMs, DMN, and Drools at AI\_dev Europe 2025](https://aletyx.ai/events/watch-aletyx-at-ai_dev-2025/) Watch our session at AI\_dev to learn the enterprise AI architecture for decision intelligence. See the powerful combination of GenAI & Symbolic AI, with Drools & DMN. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Aletyx at DecisionCAMP2025: Turn Decisions into Agents with DMN and GenAI](https://aletyx.ai/events/aletyx-at-decisioncamp-2025/) Join Aletyx at DecisionCAMP 2025 to learn how to solve GenAI's reliability gap by Turning Decisions into Agents, with leading enterprise architecture for Decision Intelligence. Topics: Events & Community, Artificial Intelligence. Reading time: 3 min ## [Essential Concepts for Navigating Enterprise AI Trends](https://aletyx.ai/blog/essential-concepts-for-enterprise-ai-trends/) Cut through the noise and buzzwords and understand the foundational concepts associated with AI, their applications, and the trade-offs enterprises must consider. Topics: Artificial Intelligence, Model Context Protocol. Reading time: 8 min ## [Automatic DMN to LLM Integration with MCP: Exclusive Aletyx Feature for Enterprise AI](https://aletyx.ai/blog/automatic-dmn-to-llm-integration-with-mcp-exclusive-aletyx-feature-for-enterprise-ai/) Bringing AI into your enterprise is no longer just about innovation—it’s about control, safety, and scale. Topics: Model Context Protocol, DMN. Reading time: 2 min --- # Partnerships Source: https://aletyx.ai/topics/partnerships/ Topic Aletyx partner announcements and the expertise those collaborations bring to customers. ## [Aletyx and Athena Decision Systems Announce Strategic Partnership](https://aletyx.ai/news/aletyx-and-athena-decision-systems-announce-strategic-partnership/) Aletyx announces strategic partnership with Athena Decision Systems, bringing enterprise builds of Drools and Kogito to European customers with expert implementation support. Topics: Partnerships, Decision Intelligence. Reading time: 2 min ## [Aletyx Announces Strategic Partnership with Indo-Sakura and UMEZO in Japan](https://aletyx.ai/news/aletyx-partnership-with-indo-sakura-and-umezo-in-japan/) Announcing our strategic partnership with Indo-Sakura Software Japan K.K. (Indo-Sakura), and UMEZO Consulting LLC (UMEZO). Topics: Partnerships, Apache KIE. Reading time: 3 min ## [Announcing Strategic Partnership with NVS Consulting: Accelerating Enterprise Innovation in North America](https://aletyx.ai/news/announcing-nvs-aletyx-strategic-partnership/) Today we announce a strategic partnership between Aletyx and NVS Consulting, combining technological capabilities with strategic expertise to help enterprises navigate complex digital transformation challenges. Topics: Partnerships, Artificial Intelligence. Reading time: 1 min --- # Process Automation Source: https://aletyx.ai/topics/process-automation/ Topic Workflow orchestration, BPMN, APIs, and practices for reliable enterprise process automation. ## [Aletyx Officially Listed as Vendor of Apache KIE](https://aletyx.ai/news/aletyx-official-apache-kie-vendor/) Aletyx is thrilled to announce our official listing as a vendor on the Apache KIE commercial support page, underscoring our commitment to the open source ecosystem and enterprise community. Topics: Apache KIE, Drools. Reading time: 3 min ## [Announcing Strategic Partnership with NVS Consulting: Accelerating Enterprise Innovation in North America](https://aletyx.ai/news/announcing-nvs-aletyx-strategic-partnership/) Today we announce a strategic partnership between Aletyx and NVS Consulting, combining technological capabilities with strategic expertise to help enterprises navigate complex digital transformation challenges. Topics: Partnerships, Artificial Intelligence. Reading time: 1 min ## [Aletyx Emerges from Stealth with Enterprise Builds of Drools and Kogito, Driving a New Era of Scalable, AI-Ready Intelligent Automation](https://aletyx.ai/news/aletyx-emerges-from-stealth-with-enterprise-builds-of-drools-and-kogito-driving-a-new-era-of-scalable-ai-ready-intelligent-automation/) Backed by Apache KIE veterans, Aletyx launches with cutting-edge builds of Drools and Kogito—bringing seamless GenAI integration, unmatched scalability, and enterprise-grade support for open-source automation solutions. Topics: Apache KIE, Artificial Intelligence. Reading time: 3 min ## [Enabling Teams with Apache KIE 10: Aletyx's Workshop on Kogito-based Workflows](https://aletyx.ai/case-studies/aletyx-workshop-kogito/) Aletyx recently delivered an Apache KIE 10 Workshop to a science and technology customer, providing hands-on training in Kogito workflows, decision modeling, and production-ready practices. Topics: Enterprise Enablement, Apache KIE. Reading time: 2 min ## [The Missing Manual for Kogito: How to Use Java APIs Instead of Auto-Generated REST Endpoints](https://aletyx.ai/blog/how-to-use-java-apis-with-kogito-process/) Learn how to trigger Kogito BPMN processes using the Java API—without relying on auto-generated REST endpoints. Topics: Enterprise Enablement, Apache KIE. Reading time: 3 min --- # Stop guessing. Learn from the architects Source: https://aletyx.ai/training/ The authority on Drools, jBPM & Kogito Most performance issues in production aren't software bugs—they are implementation errors. Equip your team with the deep internal knowledge required to build high-scale, low-latency intelligent services. [Book a Private Workshop](https://aletyx.ai/contact/) [View Curriculum](https://aletyx.ai/training/#curriculum) ## The "trial and error" method is costing you millions Drools, jBPM and Kogito are powerful, but unforgiving. We see the same story in every audit: Teams learn from outdated forums or generic consultants. They build "working" solutions that collapse under load due to: ### Engine Abuse Poorly written business logic that explodes memory usage. ### Transaction Boundaries Mixing workflow boundaries with commit boundaries, resulting in unrecoverable inconsistencies. ### Architecture Anti-Patterns Treating the Engine as a System of Record. Don't wait for a production outage to train your team. Get the architectural blueprint right the first time. ## We don't hire trainers. Our engineers teach At Aletyx, you don't get a slide-reader. You get a Core Engineer. Our workshops are hands-on and focused on production realities, not theoretical syntax. We teach you how the engine thinks, so you can make it fly. DEEP DIVE ### For enterprise teams adopting Apache KIE. Go from "evaluating" to "production-ready architecture" in one week—with the engineers who built it. A self-sufficient team capable of architecting and deploying enterprise decision and process automation. - Full Apache KIE stack: Kogito, Drools, jBPM architecture and patterns. - Decision management: DMN & DRL best practices for enterprise use cases. - Process automation: BPMN modeling, human tasks, event-driven workflows. - Production readiness: Cloud-native deployment, security, and observability. [Start Guided Pilot](https://aletyx.ai/contact/) ## Tailored to your stack. Delivered your way Private Bootcamps & Code Review: We come to you and work directly on your real problems. During the training, we tackle your specific architectural challenges, review your code, identify anti-patterns, and guide your team live on how to fix and improve them. Generic Training Vendor Aletyx Academy Teaches "How to write a rule" Teaches "How the engine processes the decision logic" Content based on outdated docs Content based on the latest Enterprise builds Instructor is a generalist Instructor is a Core Contributor/Committer Focus on Syntax Focus on Architecture & Performance Aletyx Academy Teaches "How the engine processes the decision logic" Generic Training Vendor Teaches "How to write a rule" Aletyx Academy Content based on the latest Enterprise builds Generic Training Vendor Content based on outdated docs Aletyx Academy Instructor is a Core Contributor/Committer Generic Training Vendor Instructor is a generalist Aletyx Academy Focus on Architecture & Performance Generic Training Vendor Focus on Syntax > While others profit from your confusion, Aletyx invests in your mastery. Real training, because true solutions don't need to hide behind complexity. Your last chance ## Close the knowledge gap Invest in your team's competence today to avoid technical debt tomorrow. [Schedule a Skills Assessment](https://aletyx.ai/contact/) Discuss your team's current challenges with an expert