AI Code Review
Automatically triage diffs by risk and enforce checks that can't be bypassed, keeping code reviews fast and accurate.
Risk-based grouping
AI Code Review surfaces the riskiest changes first, so reviewers know where to focus.
Required checks
AI Code Review enforces required checks that can't be bypassed.
Context-aware review
AI Code Review connects to your delivery history and knowledge graph to cite the right context.
Diff grouping by risk. Surfaces the riskiest changes first, so that changes don't get buried under noise.
Reviewer and label suggestions. The right reviewers and labels, suggested automatically.
Insights dashboards. See what got checked and flagged, across every repo.
AI checks as a required gate. Every PR runs against your organization's checks before it can merge.
No bypassing failed checks. Blocks squash-and-merge, even under deadline pressure.
Account, Organization, and Project inheritance. Set baseline checks once, then layer team-specific ones on top.
Knowledge Graph connected. Context comes from the same relationship-aware model that powers your software delivery across Harness.
Incident-aware review. A change resembling a past incident gets flagged with what triggered it and how it was fixed.
AI Code Review is built into Harness Code Repository. It evaluates every PR for risk, groups diffs by what changed, and gates merges with customizable AI checks, the way a strong tech lead would.
No. AI Code Review already works on GitHub, so you can turn it on against existing PRs without moving your source control.
Yes. AI checks are configurable at the Account, Organization, and Project level with inheritance, so platform teams set baseline checks while teams add their own on top.
It means reviews that cite your own incident history and system relationships, not just the diff. This connects AI Code Review to the Harness Knowledge Graph and is available soon.
Start with Harness Code Repository and turn on AI Code Review to gate every PR.