# Aletyx

> Enterprise decision and process automation platform.

## Docs

- [Overview](https://aletyx.ai/docs/ai-assistant/overview.md): The Aletyx AI Assistant helps you build decision models in natural language - describe what you want and it builds, changes, and explains models for you.
- [Prompts](https://aletyx.ai/docs/ai-assistant/prompts.md): Prompt ideas to try with the Aletyx AI Assistant on the Loan Pre-Qualification sample model.
- [Setup](https://aletyx.ai/docs/ai-assistant/setup.md): Subscribe to the Aletyx AI Assistant, create your API key, and connect it to the Playground - step by step.
- [Testing](https://aletyx.ai/docs/ai-assistant/testing.md): Use the Aletyx AI Assistant to generate test cases for your decision models - positive and negative, in plain language.
- [Concepts](https://aletyx.ai/docs/architecture/decisions/dmn/concepts.md): Core DMN concepts in Aletyx: DRD components, boxed expressions, decision tables, hit policies, FEEL data types, and decision execution flow.
- [Decision Services](https://aletyx.ai/docs/architecture/decisions/dmn/decision-services.md): Design, invoke, and test DMN decision services in Kogito and Drools - output and encapsulated decisions, boxed invocations, BPMN business rule tasks, and Java API calls.
- [FEEL Handbook](https://aletyx.ai/docs/architecture/decisions/dmn/feel-handbook.md): Comprehensive FEEL reference for DMN in Aletyx - data types, if/for/some/every expressions, three-valued logic, and string, list, context, and date functions.
- [Listeners](https://aletyx.ai/docs/architecture/decisions/dmn/listeners.md): Implement the DMNRuntimeEventListener interface in Kogito and Quarkus to audit, monitor, and validate DMN decision, decision table, and context entry evaluation events.
- [DMN](https://aletyx.ai/docs/architecture/decisions/dmn/overview.md): Overview of DMN in the Aletyx Enterprise Build of Kogito and Drools - DRDs, FEEL, decision tables, hit policies, and conformance level 3 support for DMN 1.1 to 1.5.
- [Decision Automation](https://aletyx.ai/docs/architecture/decisions/overview.md): Overview of decision automation with Drools - the open-source BRMS - covering DRL, rule units, DMN, FEEL, decision tables, and OOPath for declarative business rules.
- [Rule Language](https://aletyx.ai/docs/architecture/decisions/rule-language.md): Structure of a Drools DRL rule - declaration, when conditions (LHS), and then actions (RHS) - with bound variables and worked discount rule examples.
- [Decision & Process](https://aletyx.ai/docs/architecture/integration/decision-process.md): Orchestrate decisions across Kogito rule units, Drools KJAR ruleflows, and BPMN business rule tasks - with sequential, parallel, and conditional patterns over REST and Kafka.
- [Event-Driven](https://aletyx.ai/docs/architecture/integration/event-driven.md): Build event-driven rules, DMN decisions, and jBPM processes in Kogito using native Kafka and CloudEvents integration, message and catch events, and saga choreography.
- [Integration Patterns](https://aletyx.ai/docs/architecture/integration/overview.md): Integration patterns connecting Kogito decisions and processes to enterprise systems - decision-process embedding, event-driven Kafka and CloudEvents, and service orchestration.
- [Service Orchestration](https://aletyx.ai/docs/architecture/integration/service-orchestration.md): Orchestrate multi-service workflows with BPMN Service Tasks - REST and Java calls, async execution, sequential, parallel, conditional routing, error handling, and saga compensation.
- [Architecture](https://aletyx.ai/docs/architecture/overview.md): Architecture of Aletyx Enterprise Build of Kogito and Drools - the DRL, DMN, and decision-table decision engine, BPMN process engine, and rule-process integration patterns.
- [Event-Driven Architecture](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/event-driven.md): Build event-driven rules, DMN decisions, and BPMN processes with Kogito on Quarkus, using out-of-the-box Apache Kafka and CloudEvents integration for event routing.
- [Flexible Processes](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/flexible-processes.md): Model adaptable BPMN workflows in Kogito and Drools using ad-hoc processes, ad-hoc sub-processes, milestones, and ad-hoc fragments for dynamic, unstructured work.
- [GraphQL Integration](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/graphql.md): Query Kogito process instances and user tasks with GraphQL - where filters and operators, and/or logic, orderBy sorting, and limit/offset pagination.
- [Human Tasks](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/human-tasks.md): Manage BPMN human tasks in Kogito and jBPM - task lifecycle and states, user and group assignment, data mapping, forms, deadlines, notifications, and TaskService REST and Java APIs.
- [ISO-8601 Time Formats](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/iso-8601.md): How ISO-8601 dates, durations, and repeating intervals drive BPMN timer events - timeDate, timeDuration, and timeCycle - in jBPM, Drools, and Kogito.
- [Process Listeners](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/listeners.md): Process and task listeners in Aletyx Enterprise Build of Kogito and Drools.
- [Monitoring](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/monitoring.md): Monitor Kogito business processes with the Prometheus add-on and Grafana dashboards, tracking instance counts, SLA violations, and average process execution time.
- [Advanced BPMN](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/overview.md): Advanced Kogito BPMN topics - event-driven extensions, subprocesses and flexible processes, monitoring and custom listeners, GraphQL queries, and Kubernetes deployment.
- [Process Versioning](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/process-versioning.md): Manage BPMN process versioning in Kogito with the parallel deployment pattern - versioned process IDs, client routing via gateways or facades, and cleanup of completed versions.
- [Embedded](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/subprocesses/embedded.md): Embedded (inline) BPMN subprocesses group related tasks within a parent process, share its variables, and support boundary events like timers across the whole group.
- [Event](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/subprocesses/event.md): BPMN event subprocesses in Kogito - triggered by messages, timers, or errors to handle exceptions and compensation, as in SAGA-pattern order workflows.
- [Subprocesses](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/subprocesses/overview.md): Overview of BPMN subprocess types supported in Kogito - embedded, reusable, ad-hoc, and event subprocesses - for modularizing complex business workflows.
- [Reusable](https://aletyx.ai/docs/architecture/processes/advanced-bpmn/subprocesses/reusable.md): Reusable subprocesses in BPMN are standalone, parameterized processes invoked by multiple parent processes to share common logic and reduce redundancy.
- [Adaptive Process Architecture](https://aletyx.ai/docs/architecture/processes/architecture/adaptive-process-architecture.md): Adaptive Process Architecture co-locates jBPM and Kogito services on Quarkus with shared persistence, Data-Index, Jobs Service, and User Tasks for stateful cloud-native process orchestration.
- [Data Intelligence Layer](https://aletyx.ai/docs/architecture/processes/architecture/data-intelligence-layer.md): How the Data Intelligence Layer, built on the Data-Index subsystem, maintains a continuously updated snapshot of process state for real-time visibility into running processes.
- [Engine Architecture](https://aletyx.ai/docs/architecture/processes/architecture/engine.md): How the Apache KIE process engine works - the Kogito state machine powering jBPM (BPMN) and SonataFlow, with pluggable persistence (PostgreSQL, MongoDB, Infinispan, RocksDB).
- [Process History](https://aletyx.ai/docs/architecture/processes/architecture/process-history.md): How the Process History Service, built on the Data-Audit subsystem, provides a comprehensive temporal view of process execution across the lifecycle of process instances.
- [Runtimes](https://aletyx.ai/docs/architecture/processes/architecture/runtimes.md): Execution environments for Apache KIE components: Quarkus as the preferred runtime, Spring Boot as a supported alternative, and embedded Java mode for Drools.
- [Activities](https://aletyx.ai/docs/architecture/processes/basic-bpmn/activities.md): BPMN activities in Kogito - Business Rule, Script, User, Service, and Milestone tasks - with their key features, properties, and when to use each.
- [Process API](https://aletyx.ai/docs/architecture/processes/basic-bpmn/api.md): Interact with Kogito BPMN processes programmatically through the auto-generated domain-specific REST API, the technical /management REST API, and the Java ProcessService API.
- [BPMN Editor](https://aletyx.ai/docs/architecture/processes/basic-bpmn/editor.md): Configure BPMN processes in the Aletyx editor - process properties and variables, script, service, and business rule tasks for DMN and DRL, and XOR gateways.
- [End Events](https://aletyx.ai/docs/architecture/processes/basic-bpmn/end-events.md): BPMN end events in Aletyx Kogito and jBPM - None, Message, Error, and Terminate end nodes that conclude a process flow and optionally throw a message, error, or signal.
- [Gateways](https://aletyx.ai/docs/architecture/processes/basic-bpmn/gateways.md): How BPMN gateways diverge and converge process paths in jBPM - Exclusive (XOR), Inclusive (OR), Parallel (AND), and Event-based gateways for branching logic.
- [Intermediate Events](https://aletyx.ai/docs/architecture/processes/basic-bpmn/intermediate-events.md): BPMN intermediate throwing and catching events in Kogito - timer, message, signal, and compensation events for coordinating interactions within and across processes.
- [BPMN Basics](https://aletyx.ai/docs/architecture/processes/basic-bpmn/overview.md): An introduction to BPMN 2.0 basics in jBPM - flow objects (events, activities, gateways), sequence flows, and how jBPM extends the OMG notation for executable workflows.
- [Start Events](https://aletyx.ai/docs/architecture/processes/basic-bpmn/start-events.md): BPMN start events trigger a process in Kogito and jBPM - choose simple, message, timer, or signal start nodes to match how and when a workflow begins.
- [Data-Index & Data-Audit](https://aletyx.ai/docs/architecture/processes/components/data-index-audit.md): Kogito Data-Index and Data-Audit components - GraphQL querying of process state, audited event storage for compliance, plus deployment and retention options.
- [Job Service](https://aletyx.ai/docs/architecture/processes/components/job-service.md): Schedule and monitor timers, human tasks, and time-based events with Kogito Job Service - independent vs compact deployment, leader-based HA, CDC, and the Temporal Intelligence Coordinator.
- [User Tasks](https://aletyx.ai/docs/architecture/processes/components/user-tasks.md): How BPMN User Task nodes drive human-centric workflows in Apache KIE via the User Task Subsystem - assignment, delegation, lifecycle transitions, and deadlines.
- [Process Automation](https://aletyx.ai/docs/architecture/processes/overview.md): Business automation in the Aletyx Enterprise Build of Kogito and Drools - integrating BPMN workflows, decision management, and task orchestration.
- [Adaptive Process Architecture](https://aletyx.ai/docs/components/compact-architecture/overview.md): Aletyx Adaptive Process Architecture co-locates jBPM process components - Data-Index, Data-Audit, Jobs Service, User Tasks, and storage - in a single Quarkus deployment.
- [Scaling & Performance](https://aletyx.ai/docs/components/compact-architecture/scaling.md): Scale Kogito and Drools process workloads vertically and horizontally with the Temporal Event Coordinator, enabling Kubernetes autoscaling and distributed timer consistency.
- [Securing Intelligent Process Orchestrations - API Endpoints](https://aletyx.ai/docs/components/compact-architecture/securing-the-architecture.md): Secure your Intelligent Process Orchestrations API endpoints with authentication and authorization, with the example focused on Quarkus.
- [jBPM](https://aletyx.ai/docs/components/jbpm.md): jBPM, the Apache KIE Business Process Management engine in the Aletyx build - BPMN 2.0 process execution, runtime and task services, and integration with Drools, Kogito, and Quarkus.
- [Kogito](https://aletyx.ai/docs/components/kogito.md): Kogito is a cloud-native business automation platform for BPMN and DMN on Quarkus or Spring Boot, with native compilation, generated REST APIs, and Kubernetes-native deployment.
- [Model Context Protocol](https://aletyx.ai/docs/components/mcp/overview.md): Model Context Protocol governs how Drools, jBPM, and Kogito automation interacts with LLMs like Claude - a rule-governed AI gateway, context provider, prompt management, and response validation.
- [Platform](https://aletyx.ai/docs/components/overview.md): Overview of the Aletyx platform components built on Apache KIE - the enterprise builds of Drools, jBPM, and Kogito plus the Aletyx Playground, and how they work together.
- [Accelerators](https://aletyx.ai/docs/components/playground/accelerators.md): This guide provides a comprehensive walkthrough for creating, customizing, and deploying project accelerators for the Aletyx Playground.
- [Advanced Accelerators](https://aletyx.ai/docs/components/playground/advanced-accelerator.md): Create and customize Git-based Accelerators for Aletyx Playground - configure profiles, pom.xml, application.properties, Dockerfiles, CI/CD, and Kafka or Kubernetes templates.
- [Executable Processes Models: BPMN in Aletyx Playground](https://aletyx.ai/docs/components/playground/bpmn-tutorial.md): A hands-on walkthrough of exploring, modeling, testing, and deploying BPMN process models in the browser-based Aletyx Playground.
- [Components](https://aletyx.ai/docs/components/playground/components.md): Architecture of the browser-based Aletyx Playground - the Studio Environment, CORS Proxy, Extended Services, and Dev Deployment service for authoring DMN and BPMN models.
- [Customization](https://aletyx.ai/docs/components/playground/customizing.md): Customize Aletyx Playground (KIE Sandbox) - logo and favicon branding, Git provider integration, accelerators, custom commit validation, and editors via Docker and environment variables.
- [Dev Deployments](https://aletyx.ai/docs/components/playground/dev-deployment.md): Quickly test DMN and BPMN assets in containers with Aletyx Playground dev deployments, using standard or custom images - a development-only tool with key limitations, not for production.
- [Executable Rules Models: DMN in Aletyx Playground](https://aletyx.ai/docs/components/playground/dmn-tutorial.md): A 30-minute hands-on walkthrough of building and testing DMN decision models in the browser-based Aletyx Playground.
- [Playground](https://aletyx.ai/docs/components/playground/overview.md): Aletyx Playground, built on Apache KIE Sandbox, is a browser-based tool to model, test, and deploy DMN and BPMN with Git integration, dev deployments, and accelerators.
- [Playground Deployment](https://aletyx.ai/docs/components/playground/self-hosting.md): Configure a self-hosted Aletyx Playground: environment variables, Git providers (GitHub, Bitbucket), CORS proxy and extended services, custom commit validation, branding, and accelerators.
- [Core Concepts](https://aletyx.ai/docs/core-concepts.md): Core concepts of the Aletyx Enterprise Build of Kogito and Drools - how decision and process automation work, for architects and senior developers.
- [Architecture](https://aletyx.ai/docs/decision-control-tower-sidecar/architecture.md): How the Decision Control Tower Sidecar is structured — the workflow engine, process and task state, callback client, and optional integrations.
- [Decision Control Tower Sidecar — Configuration](https://aletyx.ai/docs/decision-control-tower-sidecar/deployment/configuration.md): Environment-variable reference for the Decision Control Tower Sidecar — database, callbacks, and optional integrations.
- [Decision Control Tower Sidecar — Deployment](https://aletyx.ai/docs/decision-control-tower-sidecar/deployment/overview.md): Run the Decision Control Tower Sidecar alongside Tower, with its own PostgreSQL database.
- [Customize the Promotion Workflow](https://aletyx.ai/docs/decision-control-tower-sidecar/how-to/customize-workflow.md): Adapt the Sidecar's example approval workflows to your own policy — what lives in the customizable layer, what is off-limits, and how to make changes safely.
- [Git Model Versioning](https://aletyx.ai/docs/decision-control-tower-sidecar/how-to/git-model-versioning.md): Commit the promoted model's files to a Git repository on each approved promotion — a diffable history of governed models alongside the Tower audit trail.
- [How-To Guides](https://aletyx.ai/docs/decision-control-tower-sidecar/how-to/overview.md): Guides for tailoring the Aletyx Decision Control Tower Sidecar starter — customize its workflows and actions while the Tower contract stays fixed.
- [Aletyx Decision Control Tower Sidecar](https://aletyx.ai/docs/decision-control-tower-sidecar/overview.md): A starter project for the approval workflows behind a promotion — and the workflow engine Aletyx Decision Control Tower depends on at runtime.
- [Aletyx Decision Control Tower Architecture](https://aletyx.ai/docs/decision-control-tower/architecture.md): The Tower's components, how they communicate, and how it is deployed.
- [Portal Tour](https://aletyx.ai/docs/decision-control-tower/dashboard.md): A walkthrough of the Aletyx Decision Control Tower portal: the Home landing, sidebar workspaces, masthead controls, session model, and notification surfaces.
- [Container Configuration](https://aletyx.ai/docs/decision-control-tower/deployment/container-configuration.md): Runtime requirements, environment variables, secrets, and example run commands for the Tower container.
- [Database Configuration](https://aletyx.ai/docs/decision-control-tower/deployment/database-configuration.md): PostgreSQL provisioning, Flyway migrations, and connection settings for Decision Control Tower.
- [Identity & Access Management (OIDC)](https://aletyx.ai/docs/decision-control-tower/deployment/identity-access-management.md): Configure Microsoft Entra ID or Keycloak OIDC authentication for Decision Control Tower.
- [Kubernetes & OpenShift Deployment](https://aletyx.ai/docs/decision-control-tower/deployment/kubernetes-openshift-deployment.md): Reference manifests, sidecar wiring, and OpenShift specifics for deploying Decision Control Tower.
- [Decision Control Tower — Deployment](https://aletyx.ai/docs/decision-control-tower/deployment/overview.md): Quick-start to deploy Aletyx Decision Control Tower (with its required Sidecar) locally or on Kubernetes.
- [Supported Operating Environments](https://aletyx.ai/docs/decision-control-tower/deployment/supported-operating-environments.md): Compatibility matrix for runtimes, orchestrators, databases, identity providers, and browsers.
- [Environment Management](https://aletyx.ai/docs/decision-control-tower/environments.md): Centralized access to all Decision Control environments with environment-specific configuration and governance.
- [Promotion History](https://aletyx.ai/docs/decision-control-tower/how-to/audit-trail.md): Every promotion keeps a permanent record of who requested what, who approved it, when each step happened, and the final outcome.
- [Environments](https://aletyx.ai/docs/decision-control-tower/how-to/environments.md): Browse, filter, tag, and launch the Decision Control environments you have access to from the Environments page.
- [Governance Tasks](https://aletyx.ai/docs/decision-control-tower/how-to/governance-tasks.md): The Tasks inbox is where promotion requests wait for human action - claim, approve, reject, request changes, resubmit, cancel, and annotate tasks.
- [How-To Guides](https://aletyx.ai/docs/decision-control-tower/how-to/overview.md): Task-focused guides for Aletyx Decision Control Tower, the governance portal — each guide answers a single "how do I…?" question with the shortest path to done.
- [Promotions](https://aletyx.ai/docs/decision-control-tower/how-to/promotions.md): Create, track, open, and cancel promotion requests that move a model version from one environment to another through a governed workflow.
- [Sign in & Global](https://aletyx.ai/docs/decision-control-tower/how-to/sign-in-and-global.md): How to get into the Control Tower and use the controls that are available from every screen - the Home page, the top masthead, and the collapsible sidebar.
- [Aletyx Decision Control Tower](https://aletyx.ai/docs/decision-control-tower/overview.md): Unified portal providing centralized access to all Decision Control environments, governance workflows, and audit capabilities.
- [Task Management](https://aletyx.ai/docs/decision-control-tower/tasks.md): Tasks are approval requests in the governance workflow; Aletyx Decision Control Tower provides a central view of all tasks assigned to your role.
- [Decision Control Architecture](https://aletyx.ai/docs/decision-control/architecture.md): Core architecture of Decision Control, deployment patterns, and the extended Aletyx Decision Control Tower capabilities available in the Keystone edition.
- [Deploy on AWS Marketplace](https://aletyx.ai/docs/decision-control/aws/overview.md): Aletyx Decision Control is available on AWS Marketplace with options for both rapid evaluation and enterprise deployment.
- [Sandbox Edition](https://aletyx.ai/docs/decision-control/aws/sandbox.md): The Decision Control Sandbox provides a rapid way to test and evaluate Decision Control in your AWS environment with auto-login enabled for ease of use.
- [Container Configuration](https://aletyx.ai/docs/decision-control/deployment/container-configuration.md): Runtime requirements, environment variables, secrets, and example run commands for the Decision Control container.
- [Database Configuration](https://aletyx.ai/docs/decision-control/deployment/database-configuration.md): PostgreSQL provisioning, schema management, and connection settings for Decision Control.
- [Identity & Access Management (OIDC)](https://aletyx.ai/docs/decision-control/deployment/identity-access-management.md): Configure Microsoft Entra ID or Keycloak OIDC authentication and RBAC for Decision Control.
- [Kubernetes & OpenShift Deployment](https://aletyx.ai/docs/decision-control/deployment/kubernetes-openshift-deployment.md): Reference manifests, database connectivity, and OpenShift specifics for deploying Decision Control.
- [Decision Control — Deployment](https://aletyx.ai/docs/decision-control/deployment/overview.md): Quick-start to deploy Aletyx Decision Control locally or on Kubernetes.
- [Supported Operating Environments](https://aletyx.ai/docs/decision-control/deployment/supported-operating-environments.md): Compatibility matrix for runtimes, orchestrators, databases, identity providers, and browsers for Decision Control.
- [FAQ and Troubleshooting](https://aletyx.ai/docs/decision-control/faq-troubleshooting.md): Answers to frequently asked questions and solutions to common issues encountered when using Decision Control, organized by functional area for quick reference.
- [Authoring – AI Assistant](https://aletyx.ai/docs/decision-control/how-to/authoring-ai.md): Use the in-editor AI Assistant to build, modify, and test decision models in natural language — it can edit the diagram, generate test inputs, and answer questions about the model.
- [Authoring – Models](https://aletyx.ai/docs/decision-control/how-to/authoring-models.md): Guides covering the lifecycle of a decision model in the authoring editor: creating, importing, organizing, syncing, and publishing.
- [Authoring – Testing in the Editor](https://aletyx.ai/docs/decision-control/how-to/authoring-testing.md): Test a DMN model locally with the DMN Runner before publishing — sample inputs, multiple scenarios, and saving or loading test data.
- [Home & Global](https://aletyx.ai/docs/decision-control/how-to/home-and-global.md): How to open each Decision Control workspace from the home page and use the global Settings dialog, including connecting a Git provider.
- [Management – Execute Rules](https://aletyx.ai/docs/decision-control/how-to/management-execute.md): Run published decision models with inputs and inspect their outputs.
- [Management – Units & Models](https://aletyx.ai/docs/decision-control/how-to/management-models.md): Manage the catalog of decision units, versions, and models from the Management workbench.
- [Monitoring](https://aletyx.ai/docs/decision-control/how-to/monitoring.md): Review execution history, audit logs, and analytics for deployed models.
- [How-To Guides](https://aletyx.ai/docs/decision-control/how-to/overview.md): Task-focused guides for Decision Control — each guide answers a single "how do I…?" question with the shortest path to done.
- [Prompting](https://aletyx.ai/docs/decision-control/how-to/prompting.md): Ask about and execute decision models in natural language through the conversational assistant.
- [Integration and APIs](https://aletyx.ai/docs/decision-control/integration-and-apis.md): API reference documentation, authentication patterns, integration examples, and error handling guidance for integrating Decision Control into your enterprise architecture.
- [Decision Control](https://aletyx.ai/docs/decision-control/overview.md): Centralized governance, deployment, and management for decision services.
- [Usage Scenarios](https://aletyx.ai/docs/decision-control/usage-scenarios.md): Step-by-step tutorials for common Decision Control workflows, from creating your first DMN model through promoting it to production.
- [Decisions + GenAI](https://aletyx.ai/docs/decisions-genai.md): The Model Context Protocol (MCP) pairs deterministic Drools and DMN decisions and Kogito processes with LLMs like Claude for auditable, business-owned AI outcomes.
- [AWS Marketplace](https://aletyx.ai/docs/deployment/aws-marketplace/overview.md): Deploy Aletyx Decision Control on AWS using pre-configured AMIs from AWS Marketplace with CloudFormation-based one-click deployment.
- [Sandbox Edition](https://aletyx.ai/docs/deployment/aws-marketplace/sandbox.md): Deploy Aletyx Decision Control Sandbox with an embedded H2 database for quick evaluation, proofs-of-concept, and development environments.
- [Security](https://aletyx.ai/docs/deployment/aws-marketplace/security.md): Security guidelines for deploying and operating Aletyx Decision Control on AWS Marketplace, including network, IP, and subnet best practices.
- [SSL/HTTPS](https://aletyx.ai/docs/deployment/aws-marketplace/ssl-https.md): Configure custom domains with automatic Let's Encrypt SSL certificates for secure HTTPS access to your Decision Control deployment on AWS.
- [Troubleshooting](https://aletyx.ai/docs/deployment/aws-marketplace/troubleshooting.md): Common issues and solutions for AWS Marketplace deployments of Aletyx Decision Control, including CloudFormation stack errors.
- [Amazon ECS (Fargate / EC2)](https://aletyx.ai/docs/deployment/cloud-native/ecs.md): Deploy Aletyx Enterprise Build of Kogito and Drools workloads on Amazon ECS — Fargate or EC2 launch type, with full task-definition and service examples.
- [JVM vs Native](https://aletyx.ai/docs/deployment/cloud-native/jvm-vs-native.md): Compare JVM and GraalVM Native Image deployment for Kogito decision and process services - startup time, memory footprint, scaling, and when to choose each.
- [Cloud-Native](https://aletyx.ai/docs/deployment/cloud-native/overview.md): Deploy Aletyx Enterprise Build to Kubernetes and Red Hat OpenShift, choose between JVM and GraalVM native images, and secure the Management Console.
- [Kubernetes](https://aletyx.ai/docs/deployment/kubernetes.md): Deploy a jBPM and Kogito business process automation application to Kubernetes, with step-by-step instructions and automation scripts.
- [OpenShift](https://aletyx.ai/docs/deployment/openshift.md): This guide provides comprehensive instructions for deploying Aletyx Enterprise Build of Kogito and Drools applications to Red Hat OpenShift® environments.
- [Deployment](https://aletyx.ai/docs/deployment/overview.md): Learn how to deploy Aletyx applications across cloud-native, Kubernetes, OpenShift, Docker, and AWS environments based on your product and use case.
- [First Table](https://aletyx.ai/docs/drools/decision-tables/first-table.md): Step-by-step guide to building a Drools spreadsheet decision table in Excel - defining RuleSet, RuleTable, conditions, and actions for a shipping charges example.
- [Decision Tables](https://aletyx.ai/docs/drools/decision-tables/overview.md): Set up a Drools decision tables project - Maven dependencies (drools-decisiontables, Apache POI for Excel), the .drl.xls/.xlsx/.csv naming requirement, and project structure.
- [Running Tables](https://aletyx.ai/docs/drools/decision-tables/running.md): Load and execute a spreadsheet decision table (.drl.xlsx) in Java using the KIE API, KieContainer, and KieSession, or compile it to DRL with SpreadsheetCompiler.
- [Actions (RHS)](https://aletyx.ai/docs/drools/drl/actions.md): How to write DRL rule actions in the then section (RHS) - modifying, inserting, and removing facts, logical insertions, error handling, and best practices.
- [Building Blocks](https://aletyx.ai/docs/drools/drl/building-blocks.md): The foundational components of DRL files - packages, rule units and DataStore/DataStream/SingletonStore data sources, imports, type declarations, and rule structure.
- [Conditions (LHS)](https://aletyx.ai/docs/drools/drl/conditions.md): Write Drools rule conditions (the when section): pattern matching, OOPath, constraint operators, variable binding, not/exists/forall, and accumulate and groupby functions.
- [Data Stores](https://aletyx.ai/docs/drools/drl/data-stores.md): Drools rule unit data sources - DataStore, DataStream, and SingletonStore - for typed, reactive fact handling, plus DataHandle usage and DRL examples.
- [Decision Services](https://aletyx.ai/docs/drools/drl/decision-services.md): Build a complete DRL decision service step by step using Drools rule units, data stores, salience, JUnit tests, and a REST endpoint for loan approval.
- [OOPath](https://aletyx.ai/docs/drools/drl/oopath.md): OOPath is an object-oriented XPath extension for navigating object graphs in DRL rule conditions, replacing from and collect with concise multi-level paths in Drools 10.
- [DRL](https://aletyx.ai/docs/drools/drl/overview.md): An introduction to the Drools Rule Language (DRL): what it is, why to use it, how it compares to alternatives, and where it fits in your architecture.
- [Phreak Algorithm](https://aletyx.ai/docs/drools/drl/phreak.md): How the Phreak algorithm powers rule evaluation in Drools through lazy evaluation, segment sharing, and node/segment/rule memory, and how to write more efficient DRL rules.
- [Query System in Aletyx Enterprise Build of Drools](https://aletyx.ai/docs/drools/drl/queries.md): How the Query system extracts and analyzes data from the rule engine: traditional and Rule Unit queries, parameters, backward chaining, live queries, and best practices.
- [Rule Units](https://aletyx.ai/docs/drools/drl/rule-units.md): Organize Drools rules with Rule Units - RuleUnitData classes, DataStore, DataStream, and SingletonStore data sources, queries, OOPath, and execution with RuleUnitInstance.
- [Syntax Basics](https://aletyx.ai/docs/drools/drl/syntax-basics.md): A comprehensive overview of DRL syntax: rule structure, attributes, conditions (when), and actions (then) for authoring business rules in Drools.
- [Drools 7 EOL - What you need to know](https://aletyx.ai/docs/drools/drools-7-migration.md): Drools 7 end-of-life and migration to community Drools 10 - breaking changes from session-per-task isolation, startProcess() removal, and the retirement of KIE Server and Business Central.
- [Rule Engine](https://aletyx.ai/docs/drools/engine.md): How the Drools forward-chaining rule engine stores, matches, and executes the business rules and decision models you define.
- [Getting Started](https://aletyx.ai/docs/drools/getting-started.md): Get started with Drools: understand facts, rules, working memory, and how this forward-chaining rule engine separates business logic from application code.
- [Drools](https://aletyx.ai/docs/drools/overview.md): Overview of the Aletyx Enterprise Build of Drools - the DRL rule engine, DMN decision modeling, decision tables, and Java, REST, and event-driven integration.
- [Rule Flows](https://aletyx.ai/docs/drools/ruleflow.md): Run classic Drools rule flows on Drools 10 - Aletyx Enterprise keeps the classic KieSession startProcess API working from a KJAR with the ClassicRuleFlow metadata.
- [Troubleshooting](https://aletyx.ai/docs/drools/troubleshooting.md): Aletyx Enterprise Build of Drools provides standardized messages for DRL errors to help you troubleshoot and resolve problems in your DRL files.
- [Creating Your First Decision Table in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/drools/tutorials/decision-tables.md): Walk through creating a decision table for a shipping charges calculation system, ideal for business rules managed by business analysts and subject matter experts.
- [DRL Examples](https://aletyx.ai/docs/drools/tutorials/drl-example.md): Build a shipping charges Excel decision table (.drl.xlsx) with Drools rule units, in Aletyx Playground and a Java 17 Maven project, with RuleSet and RuleTable definitions.
- [Getting Started with Drools Rule Language (DRL) in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/drools/tutorials/first-rule.md): Create a simple loan approval rule to learn the fundamental structure and components of Drools rules, from project setup to running your first rule unit.
- [Tutorials](https://aletyx.ai/docs/drools/tutorials/overview.md): Step-by-step tutorials for building your first rules and decision tables.
- [Visual Guide](https://aletyx.ai/docs/drools/visual-guide.md): A visual guide to how the Drools rule engine processes facts and rules through working memory, the agenda, and Phreak pattern matching.
- [Frequently asked questions](https://aletyx.ai/docs/faq.md): Answers to common questions about Aletyx, its products, and how to get started.
- [What is Aletyx?](https://aletyx.ai/docs/faq/about-aletyx/what-is-aletyx.md): Aletyx is an enterprise platform combining decision intelligence and process automation on Apache KIE (Drools, Kogito, jBPM), with governance and audit built in.
- [Who builds Aletyx?](https://aletyx.ai/docs/faq/about-aletyx/who-builds-aletyx.md): Aletyx is built by the original engineers behind the Drools, jBPM, and Kogito open-source projects that power rules and process automation in regulated industries.
- [Who is Aletyx for?](https://aletyx.ai/docs/faq/about-aletyx/who-is-aletyx-for.md): Aletyx serves regulated enterprises that need auditable decisions, legacy modernization, and safe AI - for both business analysts and developers.
- [What is "Accountable AI"?](https://aletyx.ai/docs/faq/concepts/accountable-ai.md): Accountable AI is automation you can stand behind: explainable, auditable, and governed decisions grounded in explicit, versioned business logic.
- [Should enterprises choose between LLMs and symbolic AI?](https://aletyx.ai/docs/faq/concepts/beyond-llms.md): Neurosymbolic AI combines statistical LLMs with deterministic symbolic rules - using engines like Drools to validate outputs for compliance, instead of choosing one.
- [What do decision tables look like for business users?](https://aletyx.ai/docs/faq/concepts/decision-tables.md): How non-technical policy owners read and manage rules as decision tables.
- [What is the difference between DMN, DRL, and BPMN?](https://aletyx.ai/docs/faq/concepts/dmn-drl-bpmn.md): How DMN, DRL, and BPMN differ: DMN models decisions visually, DRL authors rules as code, and BPMN orchestrates processes and workflows.
- [What is the difference between Drools, Kogito, and KIE?](https://aletyx.ai/docs/faq/concepts/drools-kogito-kie.md): How Drools, Kogito, and KIE relate: KIE is the foundation platform, Drools is the rules engine, and Kogito is the cloud-native runtime that packages them.
- [What AI concepts do enterprises need to understand?](https://aletyx.ai/docs/faq/concepts/enterprise-ai-concepts.md): Key AI concepts for enterprise leaders: Symbolic AI, Machine Learning, Generative AI, LLMs, and Agentic AI - and how to pair innovation with governance.
- [How can enterprises adopt AI without losing compliance and predictability?](https://aletyx.ai/docs/faq/concepts/hybrid-intelligence.md): Hybrid Intelligence combines symbolic, generative, and agentic AI - using rule-based guardrails so enterprises can adopt AI without losing compliance or predictability.
- [How do I modernize Drools applications from old versions (7.x)?](https://aletyx.ai/docs/faq/concepts/modernize-drools.md): Modernize legacy Drools 7.x applications by moving DMN, DRL, and BPMN assets onto the cloud-native Kogito runtime - without rewrites or re-certification.
- [What is BPMN?](https://aletyx.ai/docs/faq/concepts/what-is-bpmn.md): BPMN (Business Process Model and Notation) is an OMG standard for modeling business processes visually as tasks, gateways, and events - portable and executable.
- [What is DMN?](https://aletyx.ai/docs/faq/concepts/what-is-dmn.md): DMN (Decision Model and Notation) is an OMG standard for modeling business decisions visually with decision tables and FEEL - portable and directly executable.
- [What is DRL?](https://aletyx.ai/docs/faq/concepts/what-is-drl.md): DRL (Drools Rule Language) is the native, text-based language of Drools for authoring business rules with a simple when/then structure for complex inference.
- [What is Drools?](https://aletyx.ai/docs/faq/concepts/what-is-drools.md): Drools is the open-source business rules management system (BRMS) and inference engine at the heart of KIE, authoring rules in DRL, decision tables, or DMN.
- [What is KIE?](https://aletyx.ai/docs/faq/concepts/what-is-kie.md): KIE (Knowledge Is Everything) is the umbrella Apache project and shared platform behind Drools, jBPM, and Kogito, providing common APIs, tooling, and runtime.
- [What is Kogito?](https://aletyx.ai/docs/faq/concepts/what-is-kogito.md): Kogito is the cloud-native evolution of Drools and jBPM, compiling DMN/DRL decisions and BPMN processes into container-ready Quarkus microservices.
- [Why do I need to update Drools?](https://aletyx.ai/docs/faq/concepts/why-update-drools.md): Why update Drools: old versions carry unpatched CVEs, lose support after end-of-life, and miss the performance and cloud-native gains of modern runtimes.
- [How is Aletyx deployed?](https://aletyx.ai/docs/faq/deployment-pricing-support/deployment.md): Aletyx offers cloud-native, multi-environment deployment, with builds distributed through Maven and container registries.
- [What performance gains can I expect?](https://aletyx.ai/docs/faq/deployment-pricing-support/performance.md): Aletyx reports up to 30x faster execution than standard Drools, around 20% faster processing, and roughly 300% ROI over three years, depending on workload.
- [How is Aletyx priced?](https://aletyx.ai/docs/faq/deployment-pricing-support/pricing.md): Aletyx uses a predictable flat-fee pricing model with no usage-based surprises. Contact the Aletyx team for details specific to your deployment.
- [What support is available?](https://aletyx.ai/docs/faq/deployment-pricing-support/support.md): Aletyx provides community and commercial support channels plus enterprise consulting and training services.
- [Does Aletyx integrate with AI assistants?](https://aletyx.ai/docs/faq/getting-started/ai-assistants.md): Yes - Aletyx supports the Model Context Protocol (MCP), including Claude Desktop, so AI assistants can work directly with your decisions and processes.
- [What developer tools are available?](https://aletyx.ai/docs/faq/getting-started/developer-tools.md): Aletyx developer tools include a VS Code extension, an online playground, design environments, and Maven and container-registry integration.
- [How do I get started?](https://aletyx.ai/docs/faq/getting-started/get-started.md): Start building with Aletyx through the Quickstart, persona-based learning paths, or the interactive online playground.
- [How do I invoke Kogito processes with Java APIs instead of REST?](https://aletyx.ai/docs/faq/getting-started/kogito-java-apis.md): Drive Kogito BPMN processes from Java instead of REST: disable the generated endpoints and use CDI injection with the ProcessService API for full control.
- [How can analysts update decision models without waiting on IT?](https://aletyx.ai/docs/faq/products-features/ai-assistant.md): The Aletyx AI Assistant helps analysts understand DMN models, propose changes in plain language, review edge cases, and generate test scenarios with less back-and-forth with IT.
- [How does Aletyx keep AI safe in regulated decisions?](https://aletyx.ai/docs/faq/products-features/ai-safety.md): Aletyx applies deterministic AI guardrails so LLM outputs cannot override business policy, with every decision and workflow step captured in a full audit trail.
- [What is Decision Control?](https://aletyx.ai/docs/faq/products-features/decision-control.md): Decision Control is the Aletyx decision-lifecycle capability: visual multi-version DMN authoring, governance workflows, multi-environment deployment, and natural-language testing.
- [How can I connect DMN decisions to LLMs with MCP?](https://aletyx.ai/docs/faq/products-features/dmn-mcp.md): Connect DMN decisions to LLMs automatically with the Model Context Protocol (MCP) - no custom code, with guardrails that prevent hallucinations and preserve auditability.
- [Can I modernize legacy jBPM, RHPAM, or KIE Server systems?](https://aletyx.ai/docs/faq/products-features/modernize-legacy-systems.md): Aletyx is a drop-in replacement for aging jBPM, RHPAM, and KIE Server systems, letting you modernize without rewrites, behavior changes, or re-certification.
- [What products does Aletyx offer?](https://aletyx.ai/docs/faq/products-features/products.md): Aletyx offers Decision Intelligence for governed business logic and Intelligent Process Automation for compliant, auditable end-to-end workflows.
- [Cloud Command Line Tools in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/cloud-tools.md): Install and configure the Kubernetes CLI (kubectl) and Red Hat OpenShift CLI (oc) for Aletyx Enterprise Build of Kogito and Drools.
- [Container Runtime Setup in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/container-tools.md): Choose and set up your preferred container runtime environment, Docker or Podman, for Aletyx Enterprise Build of Kogito and Drools.
- [Environment Setup in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/environment-setup.md): Set up your development environment for Aletyx Enterprise Build of Kogito and Drools, covering installation and configuration of all required tools and dependencies.
- [GitHub Integration with Aletyx Playground in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/git-configuration.md): Connect Aletyx Playground to GitHub to publish projects, synchronize changes, and deploy through traditional deployment pipelines.
- [Java Installation and Configuration in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/java-setup.md): Install and configure Java 17 for Aletyx Enterprise Build of Kogito and Drools on Windows, macOS, and Linux.
- [Configuring Maven Settings for Aletyx Enterprise Build](https://aletyx.ai/docs/getting-started/maven.md): How to configure your Maven settings.xml to access the Aletyx Maven repositories for the Aletyx Enterprise Build of Apache KIE.
- [Ubuntu Environment Setup Guide for Aletyx Enterprise Build of Kogito and Drools](https://aletyx.ai/docs/getting-started/ubuntu.md): Step-by-step instructions for setting up Docker, Java 17, Apache Maven, and Visual Studio Code on Ubuntu for Aletyx Enterprise Build of Kogito and Drools.
- [Visual Studio Code® and Aletyx Developer Tools Configuration in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/getting-started/vscode.md): Install Visual Studio Code and configure the Aletyx Developer Tools extensions (BPMN and DMN editors) on Windows, macOS, and Linux.
- [Best Practices](https://aletyx.ai/docs/guides/best-practices.md): Best practices for modeling clear, maintainable, and scalable BPMN business processes in Aletyx.
- [Decisions](https://aletyx.ai/docs/guides/decisions.md): Author, test, deploy, and govern business decisions with DMN and DRL on Aletyx - deterministic, auditable logic running on Drools and Kogito.
- [Aletyx AI Assistant](https://aletyx.ai/docs/guides/getting-started/ai-assistant.md): Subscribe to the Aletyx AI Assistant, set up your token, and start working with your decision models in plain language.
- [Exploring the Aletyx Playground](https://aletyx.ai/docs/guides/getting-started/getting-started-playground.md): Navigate the documentation and find the right starting point in the Aletyx Playground based on your role and objectives.
- [Guides](https://aletyx.ai/docs/guides/overview.md): Practical guides and lifecycle documentation for building and operating decision automation systems.
- [Processes](https://aletyx.ai/docs/guides/processes.md): Orchestrate and automate long-running business processes with BPMN on the Aletyx enterprise build of jBPM and Kogito, running cloud-natively on Quarkus.
- [BPMN Examples](https://aletyx.ai/docs/guides/tutorials/bpmn-example.md): Build an employee onboarding BPMN workflow in Aletyx Playground and a Quarkus Maven project - user and service tasks, parallel gateways, boundary timers, and Kogito REST APIs.
- [DMN Accelerators](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-accelerators.md): Accelerators in Aletyx Playground are powerful templates that transform your standalone DMN models into fully structured projects ready for deployment.
- [Advanced Deployment](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-advanced-deployment.md): Deploy DMN decision services to production - JVM vs native containers, Kubernetes scaling and HPA, CI/CD, ConfigMaps and Secrets, monitoring, and security.
- [Basic Deployment](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-basic-deployment.md): Deploy a DMN model as a containerized REST decision service using Aletyx Playground dev deployments, test it via Swagger UI, and optionally deploy to OpenShift.
- [Basic Examples](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-basic-example.md): Step-by-step tutorial building a DMN model in Aletyx Playground that calculates employee vacation days from age and years of service using decision tables and FEEL.
- [Advanced Modeling](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-deeper.md): Advanced DMN modeling with Business Knowledge Models (BKMs), custom data types, list operations, hit policies, and FEEL context expressions, built through a travel insurance pricing example.
- [Introduction to DMN](https://aletyx.ai/docs/guides/tutorials/dmn/dmn-intro.md): Introduction to DMN decision modeling - Decision Requirements Diagrams, decision tables, hit policies, FEEL expressions, and executable models in the Apache KIE ecosystem.
- [Decision Modeling](https://aletyx.ai/docs/guides/tutorials/dmn/overview.md): Guide to Decision Model and Notation (DMN) with Aletyx - from building your first decision model and using accelerators to advanced modeling, deployment, and best practices.
- [Lab: Event Driven Architecture for Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/guides/tutorials/lab-eda.md): Interact with decisions and the rule engine using Kafka topics, and create processes that interact with Kafka topics using Messages nodes.
- [Lab: Let's Orchestrate Rules and Decisions in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/guides/tutorials/lab-rules-orchestration.md): Create a BPMN process that orchestrates a DMN decision and a DRL RuleUnit to validate a driver's license and evaluate traffic violations.
- [Lab: Build a process using SAGA pattern in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/guides/tutorials/lab-saga.md): Model an order process with service tasks, gateways, and compensatory actions that simulate the SAGA pattern using a data-driven flow approach.
- [Ad-Hoc Subprocesses in Aletyx Enterprise Build of Kogito and Drools 10.1.0-aletyx](https://aletyx.ai/docs/guides/tutorials/sub-adhoc.md): Ad-hoc subprocesses provide flexibility by allowing tasks within them to be executed in a non-sequential order, for scenarios where the exact sequence of activities cannot be predetermined.
- [Regulatory Compliance](https://aletyx.ai/docs/guides/use-cases/compliance.md): Automate regulatory compliance with auditable decisions and adaptive processes across financial reporting, HIPAA healthcare, and anti-money-laundering (AML) use cases.
- [Finance Use Cases](https://aletyx.ai/docs/guides/use-cases/finance.md): Finance and banking process automation use cases - loan approval, expense reimbursement, and credit risk assessment workflows.
- [Healthcare Use Cases](https://aletyx.ai/docs/guides/use-cases/healthcare.md): Healthcare process automation use cases - patient intake and triage, insurance claims processing, and treatment authorization.
- [Human Resources Use Cases](https://aletyx.ai/docs/guides/use-cases/human-resources.md): Human resources process automation use cases - employee onboarding, performance reviews, and leave request management.
- [Insurance Claims Processing](https://aletyx.ai/docs/guides/use-cases/insurance.md): Automate property and casualty, health, and fraud-investigation insurance claims with rules-based triage, risk scoring, and straight-through processing on BPM and decision management.
- [Lending Automation](https://aletyx.ai/docs/guides/use-cases/lending.md): Lending automation use cases - commercial loan approval, mortgage processing, and credit limit increases - with rules-based decisioning and BPMN process orchestration.
- [Manufacturing Use Cases](https://aletyx.ai/docs/guides/use-cases/manufacturing.md): Manufacturing process automation use cases - supply chain management, quality control, and inventory management.
- [Customer Onboarding](https://aletyx.ai/docs/guides/use-cases/onboarding.md): Automate customer onboarding with BPMN workflows and decision rules - financial services KYC/AML, telecom service activation, and healthcare patient intake use cases.
- [Industry Use Cases](https://aletyx.ai/docs/guides/use-cases/overview.md): Domain-specific patterns and real-world applications of decision and process automation.
- [Retail Use Cases](https://aletyx.ai/docs/guides/use-cases/retail.md): Retail process automation use cases - order fulfillment, customer complaint resolution, and pricing and discount approval.
- [Welcome to Aletyx](https://aletyx.ai/docs/index.md): The platform for Accountable AI — build, test, deploy, and govern business decisions and processes.
- [Cookie Policy](https://aletyx.ai/docs/legal/cookie-policy.md): How Aletyx, Inc. uses cookies and similar technologies on our website, how they work, and your choices regarding their use.
- [Product Features](https://aletyx.ai/docs/product/overview.md): Enterprise extensions and product-specific features
- [Quickstart](https://aletyx.ai/docs/quickstart.md): Choose the Aletyx getting-started path that matches your role - decision analyst or tech lead - and reach a working result quickly.
- [Quickstart for Decision Analysts](https://aletyx.ai/docs/quickstart/decision-analysts.md): Decision-analyst quickstart: model and test business decisions and processes visually in the Aletyx Playground, with no coding or installation required.
- [Quickstart for Tech Leads](https://aletyx.ai/docs/quickstart/tech-leads.md): Tech-lead quickstart: design enterprise-scale, deployable Aletyx automation, covering architecture styles and Kubernetes, OpenShift, or Docker deployment.
- [DMN Reference](https://aletyx.ai/docs/reference/dmn/overview.md): DMN technical reference for Aletyx - FEEL reserved words and select expression syntax, plus pointers to conceptual Decision Model and Notation documentation.
- [Reserved Words](https://aletyx.ai/docs/reference/dmn/reserved-words.md): Reference of DMN FEEL reserved words and keywords - logical, comparison, collection, and temporal operators, built-in data types, and variable naming rules to avoid conflicts.
- [Select Expression](https://aletyx.ai/docs/reference/dmn/select-reference.md): Reference for DMN Select expression types - Literal, Relation, Context, Decision Table, List, Invocation, Function, Conditional, For, Every, Some, and Filter, with FEEL examples and hit policies.
- [Reference](https://aletyx.ai/docs/reference/overview.md): Technical reference for the Aletyx Enterprise Build of Kogito and Drools - DMN reserved words, select expressions, release notes, plus curated books, blogs, and standards for DMN and BPMN.
- [Tech Stack](https://aletyx.ai/docs/tech-stack.md): The Aletyx Enterprise Build is a business automation platform on Apache KIE - Drools, jBPM, and Kogito - with modular architecture and flexible cloud or on-prem deployment.

## OpenAPI Specs

- [openapi](https://aletyx.ai/docs/api-reference/openapi.json)