# 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.