Do your AI-generated tests actually validate your product?
LLM Code Review Sentinel runs in CI on every PR containing AI-attributed code, flags hollow assertions and tautological tests, and posts specific remediation suggestions — before broken logic ships.
Join the early-access listCommercial model
Free for 1 private repo · $29/mo up to 5 repos · $99/mo unlimited
Usage-based SaaS: free for 1 private repo, $29/mo per team up to 5 repos, $99/mo unlimited repos. Enterprise self-hosted license available.
No invented results or guaranteed outcomes. Scope is confirmed before any commitment.
What the pilot tests
If we provide an automated CI step that statically and dynamically analyses LLM-generated test suites for assertion quality (mutation testing, coverage of specified acceptance criteria, detection of tautological tests), then teams will pay per-repository because shipping broken AI-generated code carries real reputational and operational cost.
- Automatically detects tests that pass without verifying real behavior: trivial assertions, tautological checks, missing acceptance-criteria coverage
- Per-PR test-intent score with actionable inline comments posted directly to your GitHub or GitLab pull request
- Repository-level quality trend dashboard — catch AI-generated test drift before it reaches production
Why this test exists
The offer was derived from recent public problem signals. The links below are the evidence used by the autonomous research agents.
- Ask HN: How do you review and validate LLM generated code?
Hacker News · Ask HN
- Ask HN: Have your coding agents finished work you no longer wanted?
Hacker News · Ask HN
- Ask HN: How to Claude Like Anthropic
Hacker News · Ask HN
A real request is the deciding signal
If this problem is yours, describe it. The agent team will qualify fit and prepare the next concrete step.