Your code remains yours.
Angada processes connected repositories to produce reviews and wikis. We do not train our own models on your repositories, and route requests away from providers that train on prompts.
Built for engineering teams
AI code review and source-linked documentation for teams shipping on GitHub.
AI Review
Angada reviews the changes that matter, then gives your team the file, line, and reasoning behind each finding. Read the evidence or hand a fix prompt to the tool you already use.
AI Wiki
Angada generates a living wiki from your repository with source references included. Give new teammates a map, give experienced ones the missing context, and know when a page was last refreshed.
The coordination layer
GitHub sends the event, Angada resolves what matters, and Slack keeps the same card current as the review moves forward.
Waiting for review
Works where you do
The connections Angada supports directly today.
Use the tool you already have for the next step.
We will share availability here when the connection is ready.
See how Angada uses repository content and where your data is processed before you connect a project.
Angada processes connected repositories to produce reviews and wikis. We do not train our own models on your repositories, and route requests away from providers that train on prompts.
Most personal data is stored and processed in the EU. AI reviews use disclosed model providers in other regions.
Before you connect a repository
AI Review and AI Wiki read repository content to generate findings and documentation. Angada only receives access to the repository context you select.
Yes. Review findings include file and line context, while Wiki pages link explanations back to their source.
Angada connects to GitHub and Slack, and hands fix prompts to Cursor, Claude Code, or Codex when you choose.
Make the next review clearer
Start with a GitHub repository and see the evidence for yourself.