We build machine learning models that find bugs in code. We can be used proactively as part of the development process by both humans and AI agents to eliminate problematic code before it's submitted for review. We can also do checks at time of code review through our GitHub agent that adds comments to PRs (Pull Requests - essentially just submissions of code), to ensure nothing slips through. We allow developers to enforce their own taste on the code that either the AI or their teams contribute to the codebase by providing Recurse Rules. These are written in markdown and are descriptions of bad patterns that you don't want present in your codebase (e.g. the concept of DRY - do not repeat yourself).
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