The Baz AI Code Review solution brief

A five-page brief for engineering leaders: why precision beats recall in review, how the agent pipeline reads a pull request, and how it fits the coding agents and source control you already run.

5 pages · PDF#1 in precision, Code Review Bench-26% time to merge at LSports

One document to circulate internally.

Everything a team needs to evaluate AI code review, in the order the argument is usually made: the problem, the product, the fit, and the proof.

01

Why noisy review fails

The review-bandwidth problem, and which categories of feedback developers actually act on, by rework depth.

02

What Baz AI Code Review is

Purpose-built agents that read the whole repository and its external context, and learn your team's calls through reviewer memory.

03

The integration map

A flow diagram showing where review sits: code from an engineer, Claude Code, Cursor, or Codex, landing as a PR.

04

How to roll it out

Connect a repository, calibrate on your guidelines, review in one workspace, then automate as trust builds.

05

Security and hosting

The least-privilege permission model, SOC 2 posture, and private hosting options inside your VPC or fully self-hosted.

06

Proof in production

Results from LSports, PayEm, and SpotDraft, including a #1 precision ranking on the independent Code Review Bench.

Where review sits in the flow.

From pull request to merge, one diagram.

The brief traces a pull request from GitHub, GitLab, or Azure DevOps through the agent review pipeline, resolution, and merge, so you can see exactly where each agent runs before you connect a repository.

A page from the Baz AI Code Review solution brief showing the review pipeline flow diagram

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Grounded in results from LSports, PayEm, BigPanda, and SpotDraft