AI Code Review That Runs Your Tests, Not Just Reads Them

QualityMax is an AI-native quality platform that reviews every pull request and proves
its verdict by running tests against your code and a live preview — not just commenting on
the diff. Low-noise, evidence-aware, and self-improving.

Features

Automated Pull Request Reviews

Continuously reviews new pull requests and every incremental commit, with focused analysis
across security, logic, performance, breaking changes, and testing. Each review posts a
GitHub Check Run with a clear PASS / WARN / BLOCK verdict that can gate merge.

Evidence-Backed Findings

Findings are anchored to concrete code — file and line — and corroborated by a dedicated
static-analysis pass, so reviews point at real evidence instead of vague suggestions.

Security-Focused Analysis

A dedicated SAST engine detects high-impact risks such as broken access control, command
injection, exposed secrets, dependency vulnerabilities, and unsafe code patterns.

Low-Noise Review Experience

Prioritizes believable, high-signal findings and learns from what your team dismisses, so
developers spend less time waving off false alarms and more time fixing real problems.

Pull Request Summaries

Generates a clear high-level summary of what changed in each pull request and explains why
the verdict landed where it did.

Line-Level Review Comments

Posts focused comments directly on the relevant lines of code so issues are easy to
understand, verify, and fix.

Multi-Specialist Review Engine

Combines a dedicated security engine with AI analysis across logic, performance, and
testing, merged into a single coherent review and verdict.

Test Coverage Awareness

Identifies areas where meaningful tests may be missing — especially when source changes ship
without matching coverage — and can generate and run the missing tests against your suite
and a live preview deployment.

It Runs Your Tests, Not Just Reads Them

Beyond reading the diff, QualityMax executes your native suite (Go / Rust / pytest), runs
AI-generated framework tests, and drives Playwright tests against your preview deployment —
turning "this looks risky" into "this test failed."

Team Memory

Learns from accepted and dismissed findings — including 👍 / 👎 reactions and merged-PR
outcomes — so future reviews better adapt to your team's standards and engineering
preferences.

Autonomous Bug-Fix Pull Requests

Turns production errors and tracked issues into ready-to-review fix PRs (with regression
tests) — never auto-merged, always yours to approve.

Configurable Review Preferences

Tune review categories, focus areas, and model choice per repository.