StartupSeries B
CodeRabbit
AI code review and change governance for agentic development.
CodeRabbit runs automated AI review on every pull request, posting line-level findings and committable suggestions, and has expanded into what it calls agentic change management: PR triage that prioritizes the review queue against each reviewer's capacity, change explanations and continuous security monitoring of dependencies and code health. It positions itself as an independent review and control layer as AI-generated code outpaces human review capacity. In September 2025 it raised a $60M Series B led by Scale Venture Partners at a $550M valuation, with NVIDIA's NVentures participating.
Pros & cons
Each point cites its sources and says what kind of evidence backs it. A second reviewer tried to refute every claim before it was kept.
Pros
- User reportsWidely adopted; open-source maintainers credit it as a daily reviewer and a project sponsor.[1]
- Independent testOften benchmarked as lower-noise than rivals, with about 2 false positives against Greptile's 11 in one 50-PR comparison.[1]
- DocsHas expanded beyond PR review into security deep scans and enforceable merge gates.[1]
Cons
- Independent testIn 2025 Kudelski Security turned one malicious PR into RCE on CodeRabbit's runners, leaking its GitHub App key and giving write access to about 1M repositories (since patched).[1][2]
- DocsPer-seat billing covers any developer who opens a PR in an enabled repo (Pro around $24/user/month annually), and some users object to per-user gates.[1][2]
- User reportsTeams report too much noise, especially on large PRs, and some replaced it with in-house Claude or Codex reviewers.[1][2]
- User reportsBenchmarks show it catching fewer bugs than higher-recall tools; one put it at 44% against Greptile's 82%.[1]
- Best for
- Teams that want low-friction AI PR review across many repos with a free tier for open source.
- Watch out for
- GitHub App permissions after the 2025 RCE, and per-seat costs as AI-generated PR volume grows.
Assessed Oct 29, 2026 · adversarially reviewedSuggest a correction
People
Co-founder & CEO
Comparisons & reviews
In research (4)
- CIVER: Causal Intervention Verification for Reliable Code ReviewVerdict: Incremental
Oct 26, 2026 · A commercial LLM code reviewer cited as motivation. CIVER targets exactly the false-positive noise such tools produce.
- Reva: Real-Time Vulnerability Detection through Contextual Probing of Large Language ModelsVerdict: Useful
Oct 26, 2026 · Commercial review of agent-generated code, the downstream step Reva positions itself as a cheap real-time first screen for.
Oct 26, 2026 · CodeRabbit's essay is cited among the 'keep PRs and add tooling' responses.
Oct 25, 2026 · Commercial AI code review that works on final diffs; Tracer argues review should also use the agent's trajectory.
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Connections
Relations from the Harness Hub knowledge graph, as charted in the State of Harness reports.
Sources
Verified Oct 29, 2026