Built for every engineering team.
How teams, industries and codebases use AI code review: startups, managers, enterprise, fintech, healthcare, monorepos and AI-generated code.
By team
How different teams and roles use AI code review day to day.
Startups
A senior-engineer first pass on every pull request, before you can afford to hire one — so a small team ships fast without shipping regressions.
Engineering Managers
Shorter review queues, consistent standards across reviewers, and delivery metrics — without adding process or reading every diff yourself.
Enterprise Teams
Consistent review across hundreds of repositories, with SSO, audit logs, self-hosting and your own LLM provider for data control.
Open Source Maintainers
A first review on every contributor pull request, so maintainers spend their limited time on design decisions instead of repeating the same feedback.
Security Teams
Security review on every pull request — access control, injection, secrets and your own policies — without a security engineer in every review.
Remote & Async Teams
Feedback on every pull request while reviewers are asleep, so distributed teams stop losing a day per review round to time zones.
Software Agencies
Consistent quality across every client project, with per-client rules and a review on every pull request — even when the senior engineer is on another account.
Developer Onboarding
New engineers learn your codebase's conventions from review comments on their first pull requests — without consuming a senior engineer's week.
Indian Engineering Teams
AI code review billed in INR with a GST invoice, your own LLM key at provider cost, and Indian data residency through self-hosting on Enterprise.
By industry
Regulated industries, where a bug is a financial or privacy incident.
Fintech
Catch money bugs — rounding, double charges, race conditions, missing idempotency — and enforce audit and data-handling rules on every pull request.
Healthcare
Keep patient data out of logs, enforce access control on health records, and review every change against HIPAA-style safeguards.
By codebase
Codebases with their own review challenges.
AI-Generated Code
Review code written with Cursor, Copilot and Claude Code for the mistakes AI makes — invented APIs, duplicated logic, missing checks — before it merges.
Monorepos
Different rules for each app and package, and review that sees how a change in a shared library ripples through everything that imports it.
Platform & DevOps
Review Terraform, Kubernetes manifests, CI pipelines and Dockerfiles with the same care as application code — public buckets, open security groups, leaked secrets.
Legacy Codebases
Change old code safely: review that understands the callers nobody remembers, flags behaviour changes in refactors, and guides migrations away from deprecated patterns.