Platform Overview
The governed decision platform
The InRule platform
InRule makes every regulated decision clear. Designed and proven in InRule Modeler, run at production scale by InRule Decisions, connected to your systems and AI agents by InRule Integrations. One governed lifecycle, built on the core the world’s most regulated companies have trusted for twenty years.
Trusted by leading insurers, banks, healthcare, and government organizations.
Govern complex decision logic with the confidence that every change is tested, simulated and effective in production
InRule lets organizations govern change to their most complex, regulated decision logic: ensuring the efficacy of every proposed change, capturing the approval and version record as it happens, and executing deterministically wherever their architecture requires, so growing rule complexity becomes something you govern, not something you’re afraid to touch.
Designed and proven
before it ships
Busienss teams create and modify decisions in InRule Modeler, simulate every change against real production history, and catch drift with regression testing. Errors die at design time, not in production.
Governed with one
continuous audit trail
From design, to execution, to every system and AI agent that touches a decision. One record, reconstructable on demand, not three logs to reconcile when the regulator calls.
Run deterministically,
at any scale
With full deployment flexibility, you can execute at scale deterministically in your preferred environment, and because InRule Decisions remembers every decision instance, that execution history is fully explainable throughout the entire decision lifecycle.
One governed platform, every stage of the decision
Modeler designs it. Decisions runs it. Integrations connects it.
One lifecycle, one audit trail. A decision is governed the same way at every stage..
Design time
InRule Modeler
Design it. Prove it. Govern it. Before it runs.
The workbench where business teams and developers create and modify decision logic, simulate every change against production reality, and catch drift with regression testing before anything ships.
Run time
InRule Decisions
Automate regulated decisions with complete governance.
The decision service your business runs on executes every decision at production scale, deterministically, with a governance record written the instant it runs.
Everywhere in between
InRule Integrations
Underneath every decision. Underneath every design.
The connective layer linking decisions to your systems, data, and AI agents, including the MCP servers that make governed decisions reachable from the tools your teams already use.
How it works
The governed decision lifecycle
Three stages. One loop. Every decision that runs makes the next change safer to make.
Design trusted decisions, governed by the guardrails your architects require
Business teams create and modify decision logic in plain language; architects keep approval, access, and promotion on their own terms. Every change is simulated against production history and regression-tested at real business volume before it ships.
Govern every decision as it happens, not after the fact
InRule builds governance into how the decision runs: every approval, version, and execution captured the instant it happens. Oversight isn’t a response you mount under pressure; it’s simply how the decision was made.
Run wherever your architecture requires. Deterministically.
Deploy in your cloud, fully self-hosted, or fully disconnected deployment topology is never the constraint. Every decision executes at scale with the same inputs producing the same outcome, every time.
A clear benefit is the transparency in location a specific product in each step of the process. We now just look in InRule and immediately discover its whereabouts. With the manual ways of working, you’re bound the miss steps. InRule helps ensure full compliance.
– Bart Daams, Regulatory Affairs and Compliance Manager, Toi-Toys
Change with confidence
Informed by reality
Every proposed change, simulated against production history before it ships
Compound, don’t fragment
Composable by design
Rules, machine learning, and AI as components of one platform
Point solutions fragment your investment. A rules engine here, an ML platform there, an AI pilot somewhere else, each with its own governance gap. In InRule, they compose. Deterministic rules, ML models, and AI-assisted authoring work together under one governance model, so every new capability compounds the value of what you’ve already built.
Ready for what’s next
Built for the agentic era
Accessible how your teams and their agents actually work
Reach the same governed decision through InRule Modeler’s interface, headlessly via InRule Integrations, or programmatically through agents and MCP. AI participates; the governance standard doesn’t move. And when compliance requires it, the record proves a decision ran on deterministic logic alone.
- Native interface for business authors and analysts
- REST-first APIs and SDKs for developers
- MCP servers for agents, LLMs, and tools like Copilot, ChatGPT, Claude, and Mistral Vibe
A governed decision platform designs, runs, and connects business decisions in one system. It captures an audit-ready record of every change, approval, and execution as part of running the decision itself. A traditional business rules engine only executes logic; it doesn't govern how that logic changes over time.
InRule's platform has three parts working as one lifecycle. InRule Modeler designs and proves decision logic before it ships. InRule Decisions runs it at production scale, with a governance record written the instant it executes. InRule Integrations connects it to your systems, data, and AI agents. It's one governed lifecycle and one audit trail, not three logs to reconcile later.
Yes. In InRule Modeler, analysts and subject matter experts author, modify and test decision logic visually or in plain language, without submitting it as a development ticket. Architects and IT retain approval, access, and promotion controls on their own terms, so business teams get self-service speed without IT losing the guardrails it needs.
Every proposed change is simulated against real production history and regression-tested at real business volume before it ships, so errors surface at design time, not in production.
Yes. InRule Decisions deploys in your cloud, fully self-hosted, or fully disconnected from the cloud entirely. Deployment topology is never the constraint. Every decision still executes deterministically, meaning the same inputs always produce the same, explainable outcome, wherever it runs.
This matters most for regulated organizations where data residency rules, VPC mandates, or connectivity requirements rule out SaaS-only vendors before anything else is even evaluated. Because InRule Decisions remembers every decision instance it runs, that execution history streams back to InRule Modeler as the production reality the next change gets tested against.
Rules and processes can be updated in natural language or visual models without recoding, and each proposed change is automatically tested and simulated against production history before deployment. The approval and version record is captured the instant the change happens, so it's already in place when a regulator or auditor asks, not something reconstructed after the fact.
This is what separates InRule from routing every regulatory update through a development cycle: the same governed path handles a small exception and a larger policy change without a rebuild.
Yes. InRule Integrations connects through open APIs and event-driven integrations, using a connective layer designed to fit into existing enterprise ecosystems without requiring major architectural changes.
The same layer that connects InRule to your core systems also exposes governed decisions to AI agents and tools your teams already use, so decision logic doesn't have to be duplicated or rebuilt for each new consumer.
Yes. InRule Integrations exposes governed decisions through MCP servers, so agents and LLM-based tools, including Copilot, ChatGPT, Claude, and Mistral Vibe, can reach the same decision that your native UI and REST APIs use, rather than a separate, ungoverned copy of the logic.
Whether a decision is reached through InRule Modeler's interface, headlessly via APIs, or programmatically through an AI agent, the governance standard doesn't change. The same approval history, versioning, and audit trail apply regardless of which channel touched it.
Building in-house puts your safety net in whoever built and maintains the logic. When that person leaves, so does the institutional knowledge of what the rules do and why. Legacy incumbents route even small changes through a full development cycle.
InRule makes ownership, approval, and change history part of the platform rather than one developer's memory. It gives business teams the same governed path to modify existing logic that they'd use to build something new, without a from-scratch rebuild or an IT ticket for every change.
Yes. InRule's composable architecture lets rules, machine learning, and AI-assisted authoring work together under one governance model, so teams can expand automation incrementally, process by process, without replatforming or disrupting what's already in production.
Many organizations start by governing a single decision or process and expand from there, since each new capability added shares the same governance record rather than starting a separate one.
- Business-friendly modeling so analysts can manage rules directly
- Governance tools for versioning, validation, and approvals
- Testing features to prevent errors before deployment
- Integration options that fit your architecture
- Deployment flexibility (on-premises, cloud, or hybrid)
- Clear audit trails and transparency for compliance