Govern every AI coding agent from one source of truth.
StackRails connects your code, architecture, and policy into one source of truth, serves the right slice to Claude Code, GitHub Copilot, Cursor, and OpenAI Codex through one vendor-neutral MCP server, then enforces your coding standards with three checks: before the agent writes, on the developer's machine, and at the pull request.
Most AI coding tools see the file in front of the developer. StackRails gives every agent the system around it: how services connect, what depends on what, and the standards your architects already set. The right context goes in through one vendor-neutral MCP server, and your policies are enforced end to end. Here is how it works.
Your teams already teach AI your architecture. One repo at a time.
Rules files get copied across repos and drift apart. StackRails brings your rules and architecture into one map, so your AI coding agents work from the same source.
Context rot: in a long session, the file fades.
As a session grows, the agent can lose track of rules it read early on. Researchers call this context rot. And one file can only hold the summary someone wrote, not your whole system.
When the agent asks, StackRails gives it the rules and architecture for the code it is working on. StackRails then checks the code against your rules and reports what breaks one.
- 01
Files drift across repos
Rules get copied, forgotten and contradicted from one repo to the next.
- 02
Files fade in long sessions
A rules file holds a summary, and in a long session the agent can lose track of it.
- 03
One source, checked both ways
StackRails gives context before the agent writes, then checks the code against your rules and reports what breaks one, on the pull request too.
Plugs into your enterprise stack
Reads context from where your architecture already lives, then serves the right connected slice to every agent. No migration, no duplication of truth.
AzureArchitecture
How it works
We ingest all your systems, modern and legacy: your code (modern and legacy) + legacy systems via their API endpoints + IaC + live cloud + CMDB + ADRs + event-bus. We index your code and its architecture and model your enterprise as one connected system, then serve the right slice to every AI coding agent through one vendor-neutral MCP server. We reach legacy systems through their API endpoints even when there's no source to read.
Connected Architecture
StackRails models your entire architecture. Services, APIs, dependencies, data flows, event-bus.
Connected Context
The right connected slice is fed to the agent before it generates.
Policy & Governance
Your Policy Pack enforced by three checks: before the agent writes, on the developer's machine, and at the PR.
What today's AI tools do well, and where they stop
Large Context Windows
Can hold substantial code and, combined with repo indexing, give the AI good visibility into the current project. But context windows capture code content. They don't model the relationships between components, the dependency chains across services, or what gets impacted by a change.
Retrieval (RAG)
Searches for relevant code and injects it into the prompt. Effective for finding similar patterns and relevant files. But retrieval is content-matching. It finds code that looks related, not code that is structurally connected. It can't tell you "if you change this, these three services break."
A graph-native approach
StackRails models all your systems as a graph: what calls what, what depends on what, and what a change actually breaks. So every agent reasons about the system, learns from the code you are proud of, and is held to your standards, scoped per domain and verified on every change.
1.Codebase
Multiple products Millions of lines IaC, cloud, CMDB
2.StackRails Model
Dependencies Data flows Event-bus connections
3.Curation Layer
Reference repos Pattern detection Policy discovery
4.AI Generation
Context-aware Standards-aligned via MCP
5.Code That Fits
Architecture-aligned Conformance-scored Ready for review
A governance layer wraps the whole pipeline: discover patterns, create policies, enforce through the three checks, score conformance, detect drift, audit-ready.
Free. Yours either way.See it on a real codebase. Thirty minutes.
Live walkthrough of StackRails, the three checks, and the two-tier authorization model on a real codebase. Founder-led for first customers. Response inside one business day.