AI review of every pull request, against your standards
Qualimetry reviews each pull request against your policies, principles and language standards, explains what is wrong and shows the compliant fix, and can gate merges so non-compliant code never reaches your main branches.
Every PR, reviewed against your standards
Connect GitHub, GitLab, BitBucket and Azure DevOps, and Qualimetry reviews the new code on each pull request against the standards you own.
Connect your repositories
Link your GitHub, GitLab, BitBucket and Azure DevOps repositories, and Qualimetry watches for new pull requests across your estate.
Review on every pull request
Each pull request is reviewed as it opens, with findings scoped to the new code it introduces so the author sees only what changed.
Gate the merge
A merge check reports back to the pull request and can block it, so non-compliant code never enters your main branches.
Five review perspectives
Every pull request is read against the standards you own, from five complementary angles.
Coding Standards
Checks the new code against your per-language coding standards, the concrete rules of the road for each technology.
Design & Best Practices
Weighs the change against the design guidance and best practices your organisation has agreed on.
General Principles
Holds the change to the general engineering principles that shape good code across your teams.
Secure Principles
Reviews the change against your secure engineering principles, so security is judged on every pull request.
Policies
Confirms the change honours the organisation-level policies every team is held to.
It does not just flag problems, it shows the fix
For each finding, the AI diagnoses the underlying problem, explains the rationale, and generates a standards-compliant rewrite the author can adopt.
- Diagnoses the underlying problem rather than pointing at a symptom.
- Explains why it breaches a standard so the author understands the reason, not just the rule.
- Offers a compliant example to copy that resolves the finding in your house style.
MCP tools put your standards where code is written
An MCP server exposes your standards, review findings and compliant examples to VS Code, Cursor and JetBrains IDEs, and to AI coding agents, so guidance arrives before the pull request, not after.
- Your standards, in the editor so developers can read the governing rule without leaving their work.
- Review findings and compliant examples surfaced to the IDE and to AI coding agents as they write.
- Guidance before the pull request so code is compliant by the time it is proposed.
AI code review, answered
Which platforms does it work with?
Does it review against our own standards?
Can it block merges?
Which IDEs and agents are supported?
Put an expert reviewer on every pull request
Book a demo to see AI review against your own standards, in your own workflow.