PatchSignal: Evidence-Based Verification for AI-Generated Code Fixes

AI coding tools can generate code, diagnose bugs, and propose fixes in seconds. But how do we developers know whether a proposed fix actually solves the original problem without introducing new ones?

PatchSignal is an AI-powered bug investigation and fix-verification platform that turns bug reports into evidence-backed engineering decisions.

Developers provide a repository and a bug report, PatchSignal investigates the codebase, establishes how the bug manifests, and runs reproducible checks against the affected behavior and proposed fix. Rather than trusting an AI-generated explanation or a passing test in isolation, it evaluates observable results and captures supporting evidence, including test output, logs, and relevant code changes.

Every investigation aims to produce a clear outcome: Reproduced, Not Reproduced, or Inconclusive, with evidence explaining the result. Infrastructure failures and incomplete investigations are distinguished from genuine verification results.

Our mission is to make software development with AI more reliable by adding an independent verification layer between “the AI says it is fixed” and “we have evidence that it works.”