Platform Teams

Policy-driven workflows that eliminate bottlenecks

AI made code cheap to write, and review now sets how much of it ships. LinearB shows where AI-generated pull requests stall, then routes, checks and approves them automatically, so more of what your agents write reaches production.

Trusted by the teams transforming software delivery

The constraint moved from writing code to verifying it

Agents have sped up the coding station, but reviewer capacity only grows as fast as you hire. In a software factory, the slowest station sets the output of the whole line, and today that station is review.

8.1M+

pull requests in LinearB's benchmark, from 4,800+ teams in 42 countries

LinearB 2026 Software Engineering Benchmarks Report

Find where AI pull requests stall

LinearB labels AI-assisted pull requests, so you can compare pickup, review and cycle time for AI-assisted and human-written work, by team, tool and pull request.

Label AI-assisted work

Every PR is attributed as AI-assisted or human-written, with no manual tagging.

Trend review time weekly

See whether pickup and review time are growing or falling for each team.

Find the real cause

Delays often trace to reviewer availability and time zones, not PR size.

Automate routing, approvals and AI review

AI code review scans every pull request for bugs, security issues, performance problems and spec mismatches before a person picks it up. Workflow automation routes each change and approves the ones your teams define as low-risk.

AI review on every PR

Runs independently of the tool that wrote the code.

Risk-based routing

Send each change to the reviewer who owns that code.

Auto-approve low-risk changes

Clear the changes your teams define as safe, without waiting on a person.

Automate routing, approvals and AI review

Enforce AI governance as code

LinearB is the only engineering productivity platform that lets you standardize, enforce and adapt AI policies. Write the rules once as policy-as-code and apply them on every pull request.

Route AI PRs to specific reviewers

Send AI-generated changes to the people who should see them.

Extra approval for agent commits

Require a human sign-off before agent-authored code merges.

Stricter testing where it counts

Apply tighter checks to the changes that carry the most risk.

Expedia reinvests 2,000 developer hours a month

Expedia runs more than 3M automations with LinearB, including 200K+ pull request automations, and reinvests 2,000 developer hours every month.

2,000

developer hours reinvested monthly

What you'll report on

Pickup time

Flow Efficiency: how long a pull request waits before review starts.

Review time

Flow Efficiency: how long review takes, from first comment to merge.

Cycle time

Flow Efficiency: first commit to production, broken down by stage.

PR size

How much each pull request asks of its reviewer.

Automation coverage

The share of pull requests your workflow rules route, check or approve.

AI vs. human split

AI Leverage: how much of your merged work is AI-assisted.

If the pickup time is two days, the person has already forgotten what they worked on two days ago. Our target is eight hours, so everyone reviews a PR within business hours, and you merge while the PR is still fresh.

Deni Spasovski

Engineering Chief of Staff, Emburse

Related use cases

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Cycle Time

Turn faster coding into faster delivery

Learn more