Best human baseline
~90%
Share of review comments from your best human reviewers that lead to real code changes. First-party observation from Releezy Guardian, sample size pending publication.
Releezy Guardian, in our own data
Releezy Guardian
The scoreboard for every reviewer — human or agent.
See, in one number, whether each reviewer on your team actually improves the code. Releezy Guardian computes it from your own git history — no self-reported metrics, no vendor benchmarks. Your best human reviewers set the baseline; everyone else is measured against them.
This is the metric nobody else reports: reviewer effectiveness. It tells you whether a comment produced a fix or got ignored. Over time, it becomes the clearest signal you have about the health of your team — and the AI tools you pay for.
The product
Your whole team, on one scoreboard.
Every repository gets a live health score, PR flow analytics, and a per-reviewer effectiveness number — so you know at a glance where review is working and where it isn't.
Releezy Guardian — organization overview.
What Guardian sees on real repositories.
The gap between what humans achieve and what AI tools achieve on code review is bigger than vendors admit. We show it.
AI tool range
30–60%
Most AI code review agents land between 30% and 60% effectiveness on organic pull requests. The spread between tools is larger than the average.
Releezy Guardian, in our own data
The verification gap
96% / 48%
96% of developers do not fully trust the code their AI tools produce. Only 48% verify before committing. The gap between distrust and verification is the governance problem.
Sonar, 2026 State of Code Developer Survey (1,149 developers)
Acceptance gap (independent)
84.4% 32.7%
An independent study of 8.1 million pull requests across 4,800 engineering teams found AI-generated PRs are accepted 32.7% of the time. Human-written PRs: 84.4%. Two-thirds of AI PRs need significant rework.
LinearB, 2026 Software Engineering Benchmarks
How the ruler works.
One metric, computed deterministically, applied to every reviewer without exception.
01
Connect your git repository.
Releezy Guardian reads your pull request history, review comments, and code changes. Read-only. Your code never leaves your repository.
02
The baseline emerges.
Guardian identifies your strongest human reviewers and computes how often their comments produced real code changes. That number — around 90% for the teams we have observed — becomes your ruler.
03
Every contributor is measured against the baseline.
Copilot, Cursor, CodeRabbit, Releezy Reviewer, every human — they all show up on the same scoreboard. One number per contributor. No vendor exemptions.
See where your team stands.
A 30-minute demo on your repository. You will see your ruler on day one.
Releezy Suite
Meet every product.
Releezy Guardian
The scoreboard.
Discover the truth about who writes and who reviews code on your team — human or AI. No guessing. No surprises on your next deploy.
Open GuardianReleezy Loop
The governed harness.
Picture your senior engineers back to architecture, while AI agents handle the repetitive work — under governance, audit, and spend control.
Open LoopReleezy Reviewer
The customized code reviewer.
A code reviewer that already knows your project rules — measured shoulder to shoulder with your humans from the first comment.
Open ReviewerReleezy Plan
The discovery agent.
First, the right problem. Then, the code. The discovery agent turns real user signal into a backlog worth building.
Open PlanReleezy Advisor
Agentic-readiness assessment.
Advisor runs a deep, multi-agent analysis of any repository and scores how ready it is for AI-agent work — then turns every gap into an actionable issue.
Learn more