Governed tools for AI agents
Expose your workflows to Claude, Cursor, and ChatGPT over MCP. Every AI gets its own token, scoped to the exact rulesets, files, and logs you allow — and nothing more.
Rules · Multi-model AI · AI agents — one governed workflow engine
Give your AI agents tools you can trust
AI Rule Engine turns your business logic into governed, auditable workflows — then lets Claude, Cursor, and ChatGPT trigger them through the Model Context Protocol with the exact permissions you grant. Combine deterministic rules, multi-model AI, and human approval in one place.
Deploys in your own Azure tenant · Your prompts and data never leave your cloud · Every run is logged and auditable
What makes AI Rule Engine different
Multi-model AI, kept predictable
Use Anthropic, OpenAI, Azure OpenAI, Gemini, or xAI inside rules that stay deterministic and auditable. Pick the right model per step without rewriting your logic.
Humans stay in the loop
Pause any workflow for human review and approval before it acts. AI proposes, your team decides on the decisions that actually matter.
Your cloud, your data
Deploy into your own Azure subscription so prompts, data, and execution history never leave your tenant. Pair it with Azure OpenAI for an end-to-end private setup.
Detailed Feature Overview
Multi-model AI, no lock-in
Call text generation, vision, image generation, speech, and content moderation from any rule — and pick the right model per step across Anthropic, OpenAI, Azure OpenAI, Gemini, and xAI. Switch providers with a config change, not a rewrite.
AI runs inside conditions you control, so personalization, classification, and moderation all happen on logic that stays deterministic and auditable.
Runs in your cloud, not ours
AI Rule Engine installs into your own Azure subscription, so prompts, data, and execution history never leave your tenant. You get Azure's scale, reliability, and security with full control of your data — and pairing it with Azure OpenAI keeps model calls inside your boundary too. The answer to “where does our data go?” is simple: nowhere.
Deterministic rules you can read
Build RuleSets with nested conditions and reusable actions, no code required. Trigger them from API calls, schedules, or AI agents, and define the logic in an interface your whole team can follow.
Actions reach across AI calls, logging, and external APIs — so the same engine handles a simple notification and a multi-step business process, and you can always see exactly why it decided what it did.
Trigger from any system
A secure, high-performance API lets your existing apps fire rule execution in real time. Drop AI Rule Engine into the systems you already run and make data-driven decisions where the work actually happens — no new platform for your team to live in.
Long-running work, handled
Waiting on a slow API, a large dataset, or a human approval should not block everything else. Asynchronous tasks let workflows pause and resume without holding up the queue, so the system stays responsive while the slow parts finish on their own time.
Extend it to fit your stack
Wrap your own logic in custom extensions and call them straight from your rules. Add new actions, conditions, and data sources so the engine matches how your business actually works — instead of forcing your process to match the tool.
Bring AI assistants into real workflows with MCP
AI Rule Engine supports the Model Context Protocol (MCP), so AI assistants can initiate workflows, read approved files, inspect ruleset run logs, and trigger broader automation through the workflows you already define.
You control permissions for each AI instance individually, and you can set up your own MCP server in minutes to expose only the workflow actions, files, and logs that fit the job.
Teams putting AI into production trust AI Rule Engine
Governed agent tools, multi-model AI, human approvals, and a deployment that stays in your own cloud — here is what that looks like in practice.
Frequently asked questions
What is AI Rule Engine?
AI Rule Engine is a cloud platform that turns your business logic into governed, auditable AI workflows. AI agents like Claude, Cursor, and ChatGPT can trigger those workflows through the Model Context Protocol (MCP) using only the permissions you grant.
How do AI agents use AI Rule Engine?
You expose your workflows and tools as MCP tools. Connected AI agents call them like any other tool, but every call runs inside the permissions, validation, and approval rules you define, and every run is logged for auditing.
Which AI models does AI Rule Engine support?
AI Rule Engine is multi-model and works with Anthropic (Claude), OpenAI, and Google models, so you can choose the best model for each step or switch providers without rebuilding your workflows.
Does AI Rule Engine support human approval?
Yes. Human-in-the-loop approval is built in. You can require a person to review and approve high-risk actions before a workflow continues, while low-risk steps run automatically.
What can I build with AI Rule Engine?
Common uses include support ticket triage, lead scoring, document classification, invoice and quote approvals, fraud and compliance review, and customer onboarding. The use cases page covers 20 detailed examples.
How much does AI Rule Engine cost?
AI Rule Engine offers a free tier plus paid plans for dedicated environments and shared hosting. See the pricing page for current plans and limits.
Ready to automate a real workflow?
Build your first governed AI workflow today, then connect the agents and apps that should run it.