For GitHub teams reviewing coding-agent PRs
Reviewz turns observable GitHub PR signals into advisory review plans: what needs attention, where to start, how deep to review, and what evidence is missing.
Selected repositories only. No code or branch changes. Human reviewers keep the final decision.
Sample output
The reviewer still has to ask:
#1842
Deep reviewAuth middleware touched with weak regression evidence.
#1839
Lightweight reviewCopy-only UI change. CI green. No sensitive files.
#1835
Specialist reviewBilling calculation and migration logic touched.
#1831
Standard reviewAPI response shape changed with tests present.
PR #1842 — Deep review recommended
Illustrative example, not customer data. Reviewz guides attention; final review stays human.
Reviewz gives reviewers a clear path into the PR, before they spend time reconstructing the risk themselves.
Start with one selected repository. No install required to request access.
Beta access
Request private beta access to review real GitHub pull requests with advisory guidance.
Selected beta teams start with real GitHub pull requests from one repository.
Reviewz scans recent PR activity, produces a guided PR queue, and walks your team through priority, review depth, start files, and missing evidence.
The beta is best for GitHub teams using or piloting coding agents in PR-based workflows, especially when PR volume, stacked changes, or evidence gaps create review load.
The private scan turns recent PR activity into a review triage snapshot.
Recommended next step: open the guided view for the first PR needing attention.
Illustrative example, not customer data.
No install is required to request access. Selected teams review permissions before connecting repositories.
Problem
Agents made code generation faster. They did not make review ownership easier.
They create branches, modify files, add tests, draft pull requests, and keep working in parallel. Your team is limited by how clearly humans can decide what to review next.
Agents increase the number of branches, diffs, and pull requests your team has to inspect.
"Tests added", "behavior unchanged", and agent summaries are context, not proof.
GitHub shows the queue. It does not tell your team where human attention belongs.
How it works
Start with the repos where agent-authored PR volume is already visible.
Reviewz analyzes PR metadata, branch information, diff structure, touched files, checks, tests, labels, ownership signals, and evidence available in GitHub.
Each PR is classified by actionability and review depth.
The output can appear in the PR workflow as an advisory GitHub Check in the existing review workflow.
Reviewz recommends where attention belongs. The reviewer keeps authority.
Reviewers can mark guidance as useful, too cautious, not cautious enough, low signal, or wrong starting point.
The workflow stays familiar.
The review plan becomes clearer.
Product
For every pull request, Reviewz produces a focused advisory review plan.
Not a wall of comments. Not a final review decision. Not another dashboard your team forgets to open.
A focused review guide inside the GitHub workflow.
Which PRs need human attention first, and which can wait.
Whether the PR needs lightweight, standard, deep, or specialist review.
The first file, area, or objective a human should inspect.
What is observable, what is missing, and the next useful human step.
Reviewz does not replace review.
It makes the first human review sharper, faster, and easier to defend.
Category
You do not need another bot commenting every line.
Most AI code review tools answer one question: what did the model find in this PR?
Reviewz answers a different question: what should a human reviewer do next?
When agent-authored PR volume grows, the limiting factor is not only issue detection. It is attention allocation: which PR deserves deep review, which one can be handled lightly, where to start, and what evidence is still missing.
AI code reviewers comment on code. Reviewz guides the human review plan.
Scanners verify rules. Reviewz helps decide where reviewers should look.
GitHub organizes pull requests. Reviewz organizes attention.
Code review bots tell you what they found. Reviewz tells you what a human should do next.
For teams
Reviewz is for teams that already feel the review bottleneck created by coding agents.
See which PR needs attention, where to start, and what still needs verification.
Give the team a shared triage language for PR attention, depth, and review ownership.
Reviewz is for teams that want the speed of agents without losing the discipline of human review.
FAQ
Reviewz is a guidance layer for human reviewers.
No.
Reviewz is a guidance layer for human reviewers.
AI code reviewers usually generate comments, summaries, and issue suggestions. Reviewz focuses on a different question: what should the human reviewer do next?
No.
Reviewz can sit above those tools.
CI, SAST, linters, and AI reviewers produce useful signals. Reviewz helps translate those signals into review priority, review depth, evidence gaps, and human action.
Reviewz is advisory-first.
Its role is to guide human review, not to take final authority.
No.
Reviewz is intentionally not designed as a high-volume inline comment bot.
The core output is a focused advisory review plan: review depth, start-here file, reason, evidence present, evidence gap, and human action.
We review GitHub workflow fit, coding-agent usage, PR volume, and review bottleneck intensity.
Selected teams review GitHub App permissions before connecting repositories, then start with one selected repository and advisory guidance for real pull requests.
Reviewz helps your team know which PRs deserve attention first, how deeply to review, where to start, and what evidence to verify before human review.
Agents write.
Reviewz guides.
Humans decide.
Request beta access for your GitHub team.
Private beta
Request beta access for your GitHub team.
Share one GitHub repository or organization and how your team uses coding agents. We review fit and reply with next steps.