Korbit AI

Korbit AI reviews pull requests on GitHub, GitLab, and Bitbucket to catch issues, generate clearer PR descriptions, and create review summaries.

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Overview

Korbit is an AI code review tool for GitHub, GitLab, and Bitbucket that reviews pull requests with repository context. It analyzes diffs, comments on issues it finds, and can help teams move through review cycles with fewer manual steps.

The product also generates PR descriptions, review summaries, and team reports through Korbit Insights. The site positions it as a workflow tool for developers and engineering teams that want faster reviews, clearer PR context, and automated summaries without giving up human approval.

Core features

Context-based PR review

Reviews pull requests with project context so feedback is tied to the codebase rather than isolated diff lines.

Actionable review comments

Flags code issues and explains how to fix them, with comments posted directly inside the pull request.

Multi-platform support

Supports GitHub, GitLab, and Bitbucket so teams can use it in their existing repository workflow.

Automated PR writeups

Generates PR descriptions and review summaries to help reviewers and managers understand changes faster.

Flexible review modes

Offers both automatic and manual reviews, plus comprehensive and essential review modes on the Pro plan.

Team reporting and insights

Provides Korbit Insights for reports such as release notes, sprint reviews, stand-ups, and 1:1 summaries.

Common use cases

Pre-review pull request screening
Use Korbit to review pull requests before teammates spend time on manual review, so obvious bugs and code quality issues are caught earlier in the workflow.
PR context and handoff
Use the generated PR description and review summary to give reviewers faster context on what changed and why it matters.
Team reporting and documentation
Use Korbit Insights to create release notes, sprint reviews, stand-up reports, and 1:1 summaries without assembling them manually.
Developer upskilling
Use the feedback loop and code suggestions to help developers understand fixes and learn patterns from the review comments they receive.
Enterprise rollout
Use the enterprise option when a larger organization needs custom billing, additional security checks, or on-prem installation.

Pros and Cons

Pros

Works directly inside GitHub, GitLab, and Bitbucket.
Finds issues and explains suggested fixes in the pull request.
Can generate PR descriptions, review summaries, and team reports.
Offers a trial and multiple plan levels, including an enterprise option.
States that private code is not used to train models and describes security controls on the trust page.

Cons

Pricing details for some use cases are only partially visible, and Enterprise pricing is custom.
The product description is focused on PR review and reporting, so broader DevOps or issue-tracking capabilities are not clearly supported from the source.

FAQ

How does Korbit fit into a pull request workflow?

Korbit reviews pull requests directly in GitHub, GitLab, and Bitbucket. It analyzes diffs with project context, posts comments back to the PR, and can also generate PR descriptions and review summaries.

What pricing options does Korbit offer?

The pricing page shows a 14-day free trial for all plans. It also lists Pro, Max, and Enterprise options, with Pro and Max available on annual or monthly billing and Enterprise billed annually.

How does Korbit handle code privacy and security?

Korbit says it does not use private code to train its models. The security page also states that code is handled with TLS in transit, a zero-day retention policy with its model providers, and SOC 2 Type II compliance.

Which repositories and platforms can Korbit access?

Korbit can be used with GitHub, GitLab, and Bitbucket, and the pricing page notes that repository access can be limited during setup. The product is designed to work inside an existing Git PR workflow.

Who is Korbit best suited for?

Korbit is aimed at teams that want automated review assistance, PR summaries, and codebase-aware feedback before human review. The pricing page also notes an enterprise option for larger organizations and custom requirements.