• Recurse ML is an AI-driven platform for code review and quality assurance.
• It assists developers in identifying, understanding, and fixing bugs before deployment.
• Utilizes machine learning models specialized in analyzing source code to detect subtle errors and comprehend full codebase context.
• Offers actionable suggestions for code improvement.
• Seamlessly integrates with GitHub pull requests and provides a local CLI tool named `rml`.
• Compatible with AI-assisted coding workflows such as Cursor and Claude Code.
• Adheres to a zero-retention privacy policy, ensuring data security.
• Aims to enhance debugging speed, increase confidence in code quality, and shorten review times.
Intelligent full-codebase analysis
Machine learning-based bug detection
Automatic pull request reviews
Integration with GitHub workflows
Local CLI tooling via `rml`
Compatibility with AI coding assistants
Expert knowledge of external libraries
Customizable coding rules and standards
Real-time feedback on breaking changes
Zero-code retention privacy policy
What is Recurse ML and what does it do?
Recurse ML is an AI-powered code review platform that uses machine learning to detect bugs, enforce rules, and provide intelligent suggestions across your codebase.
How does Recurse integrate with development workflows?
It can run automatically in pull requests via GitHub, be used locally with the `rml` CLI, or connect to AI code assistants like Cursor or Claude Code for real-time checks.
Does Recurse store or train on my private code?
No—Recurse enforces a strict zero-retention policy and does not keep or reuse your proprietary code for model training.
Which programming languages does Recurse support?
Recurse is designed to work across major languages and ecosystems, understanding library semantics to catch nuanced bugs in diverse codebases.
Can Recurse enforce custom coding standards?
Yes—teams can define custom rules and standards, and Recurse will apply them automatically across commits, PRs, and CI workflows.