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CodeDig
Live PR risk and blast-radius analysis for teams that want to understand downstream impact, coverage gaps, API changes, and security findings before merge.
Overview
CodeDig is an AI-assisted code intelligence platform that helps engineering teams understand the risk of a pull request before it merges.
It is built for the practical questions that slow teams down during review:
- What changed?
- What downstream systems or consumers might be affected?
- Are there public API changes?
- Are the changed paths covered by tests?
- Did the PR introduce security-sensitive patterns?
- Is this safe to merge, or does it need a deeper look?
Website: codedig.ai
GitHub integration: CodeDig GitHub app
GitLab support: Available
Status: Live / active
Key Features
PR Risk Analysis
CodeDig summarizes pull request risk with a practical review signal instead of another wall of raw diff output.
It looks at changed files, affected paths, likely downstream impact, and review-sensitive areas so teams can quickly tell whether a PR is routine or needs more attention.
Blast-Radius Awareness
The core idea is simple: before a merge, teams should know what else might break.
CodeDig helps identify downstream consumers, public API changes, and architectural touchpoints that may not be obvious from the diff alone.
Security Scanning
CodeDig flags security-sensitive findings during review so teams can catch issues before they ship.
The goal is not to replace security review. It is to make risky patterns more visible at the point where developers are already making merge decisions.
Architectural Intelligence
Beyond single-file linting, CodeDig is designed to reason about architecture and system impact.
That makes it useful for platform engineering teams, security-conscious organizations, fast-growing startups, and enterprise development teams where a small PR can have a larger blast radius than it first appears.
GitHub and GitLab Workflows
CodeDig supports modern code review workflows across GitHub and GitLab, with analysis designed to fit where teams already review code.
Why I Built It
Most review tools are good at showing what changed. Fewer tools help teams understand what the change might affect.
That gap matters most when teams are moving quickly, systems are interconnected, and reviewers do not have the full architecture in their heads.
CodeDig is my answer to that problem: a practical AI-assisted review layer that helps teams merge with more context and fewer surprises.
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