Revieko is an AI-powered GitHub App that identifies architectural drift and structural risk hotspots in pull requests.
Revieko is a GitHub App designed to make architectural drift visible within pull requests. It learns a repository-specific baseline from historical data and then surfaces structural risk hotspots in every PR comment. This allows reviewers to focus on critical changes without sifting through thousands of lines of code, shortening the time-to-trust for new code, including AI-generated changes. The tool provides a high-signal attention map, highlighting the most important lines to review first. It focuses on structural deviations like new abstractions, boundary shifts, hidden coupling, and increased control-flow complexity, rather than cosmetic issues or linting noise. Revieko integrates directly into the PR workflow, offering a risk summary, top hotspots, and per-file actions, with configurable policies (warn, require changes, pass) and detailed reports available in HTML, Markdown, or JSON formats. Revieko uses structural machine learning to analyze code as structural complexity, not natural language. It scores deviations against the repo's baseline, providing targeted insights into where architectural judgment is most likely required. It is designed to reduce cognitive load for developers, tech leads, and engineering managers by making structural changes observable and helping maintain architectural consistency as codebases evolve.
Integrations: GitHub
Platforms: Web, GitHub App
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