StackRails gives AI coding agents enterprise context
StackRails is building an architectural model of enterprise systems that AI coding agents can use before making changes. The platform also checks pull requests against a company's engineering policies.
- StackRails maps dependencies between code and systems.
- AI agents receive enterprise architecture and policy context before writing code.
- The platform checks pull requests against company policies.
- StackRails works with agents from Copilot, Claude Code and Codex.
- The product is already available.
Changes can easily break in large codebases
According to StackRails founder Alexander Wheeler, the company's engineers push the limits of AI-powered coding every day across large and complex codebases. The company began using AI tools early, then found that in codebases spanning multiple repositories, AI agents repeatedly produced changes that broke other parts of the system.
They built StackRails around this problem. The service uses proprietary graph technology to map how code and systems depend on one another within an enterprise. This gives AI agents the context of the architecture and the company's policies before they write any code.
It connects system components in a single model
StackRails organizes code, infrastructure, APIs, data flows, documentation and engineering policies into a single architectural model. This shows how systems work together and what impact a particular change could have.
Through the StackRails extension, coding agents can access this knowledge. The goal is for new code to fit into the existing codebase and avoid creating poor design decisions or so-called shadow code.
The platform checks every pull request against company policies and flags changes that could cause problems. Repository settings determine whether a failed check blocks the merge. StackRails also runs AI-powered architecture reviews that look for technical risks and policy violations, while suggesting fixes.
It complements existing AI tools
According to StackRails co-founder Magnus Backström, companies already pay for AI coding tools, while StackRails makes them more effective. The service works with agents such as Copilot, Claude Code and Codex, giving them knowledge of the company's own systems before they write code.
Over time, Backström says, this could mean engineers spend fewer hours and tokens remapping the codebase or fixing changes that cause problems later. According to a StackRails statement, fewer rewrites may be needed at the end of the process before code reaches production.
Mapping the entire system also provides another benefit: up-to-date documentation of the enterprise architecture. Alexander Wheeler says this allows any team member to ask their coding agent how part of the system works, so the knowledge is not limited to the one or two people who originally built it.
StackRails' product is already available. The company will share more details at the Gartner IT Symposium/Xpo event, held from November 9 to 12 at the International Convention Center in Barcelona.
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