Best AI Code Review Tools (2026): 11 Reviewers Compared

AI coding assistants have made writing code faster, but somebody still has to check it. Pull requests pile up, reviewers skim, and small mistakes slip into production because there wasn't time to read every line carefully.

The eleven AI code review tools below are listed alphabetically and in no particular order, and every description comes from the vendor's own website, read this week. If you'd like to try AI review with a chatbot first, my AI prompts for code review are a quick way to start.

AI code review tools side by side

I checked the free plan column on each tool's own website, as of Oct 2026. Yes means the site names a free plan, a free version, a free allowance, freeware or an open source version. Trial only means a time-limited trial. Not stated means the pages I read named neither, even where the software is widely known to be free or there's a button inviting you to start, so check the vendor's page before you rely on it.

Tool	Type	Good for	Free plan
Bugbot	AI code review from Cursor	Teams already coding in Cursor	Not stated
CodeRabbit	AI review and governance for agentic development	Reviewing code written by AI agents	Trial only
cubic	AI code review for complex codebases	Large, complicated repositories	Yes
DeepSource	AI code review platform	Reaching production with confidence	Trial only
Greptile	AI code review with full codebase context	Catching bugs across a whole repo	Yes
Kodus	Open source AI code review	Self-hosting with your own model key	Yes
Korbit	AI code reviews across Git hosts	Teams split across GitHub, GitLab and Bitbucket	Trial only
Mesrai	AI code review that maps your architecture	Monorepos and multi-repo setups	Trial only
Qodo	Multi-agent AI code review	Enforcing team standards on every change	Trial only
Sourcery	AI code review and security scanning	Strict reviews that catch the small stuff	Trial only
What The Diff	AI pull request summaries and review help	Explaining changes to the whole team	Not stated

Eleven AI code review tools to try

Bugbot

Best for: Teams already writing code in Cursor who want AI code review built for production pull requests from the same company.

CodeRabbit

Best for: Teams shipping lots of AI-written code who want review, security and prioritisation of changes before they merge.

cubic

Best for: Engineering teams with complex codebases who want AI reviews, with a free starter tier and free use for open source teams.

DeepSource

Best for: Growing teams that want an AI code review platform with a free trial and no credit card needed to start.

Greptile

Best for: Developers who want reviews that understand the whole codebase, with a free starter plan for a single developer.

Kodus

Best for: Privacy-minded teams who want open source AI review they can self-host, using their own model and key with no markup.

Korbit

Best for: Companies using GitHub, GitLab or Bitbucket who want AI code reviews that work on all three, starting with a free trial.

Mesrai

Best for: Tech leads with monorepos or several repositories who want reviews that understand how the whole architecture fits together.

Qodo

Best for: Organisations that want multi-agent review to enforce their own coding standards, with free use for open source projects.

Sourcery

Best for: Perfectionist teams who want AI review plus security scanning, with free use for open source projects and trials on its other plans.

What The Diff

Best for: Busy teams who want each pull request turned into a clear update that explains the change to everyone, not only the reviewer.

Where to start for your situation

• A single developer starting free: Greptile.
• Self-hosting with your own model: Kodus.
• Teams already coding in Cursor: Bugbot.
• Lots of code written by AI agents: CodeRabbit or Qodo.
• Complex codebases and monorepos: Mesrai or cubic.
• GitHub, GitLab and Bitbucket together: Korbit.
• Strict reviews plus security scanning: Sourcery or DeepSource.
• Explaining changes to the whole team: What The Diff.

An AI reviewer sees your code, so check where it goes

The National Cyber Security Centre's guidelines for secure AI system development aim to help providers build AI systems that function as intended, are available when needed and work without revealing sensitive data to unauthorised parties.

Apply the same thinking when you connect a reviewer to your repository. Ask where your code is processed, whether it's used to train models and who can see the review comments, especially for client work.

AI review alongside human review

AI reviewers are quick and tireless. They catch missing checks, inconsistent naming and common security slips in seconds, which frees people to spend their time on design and logic.

They don't know your business the way your team does, though. Keep a human approval on every change that matters, and treat AI comments as a second pair of eyes rather than the final word.

Questions to ask before you connect an AI reviewer

1. Does it work with GitHub, GitLab or Bitbucket?
2. Can I self-host it or use my own model key?
3. Is my code used to train models?
4. Can I teach it my team's coding rules?
5. How noisy are its comments on a typical pull request?
6. Does it include security scanning as well as review?

The wider list, including tools without AI, is in our code review tools roundup.

Signs your team could use an AI reviewer

• Pull requests wait days for review. Get a first pass instantly.
• AI assistants write much of your code. Check it as fast as it's written.
• The same mistakes keep coming back. Turn them into rules.
• Reviewers skim large changes. Let AI summarise them first.

Do you make an AI code review or developer tool? Tool makers can ask to be considered for a featured place on this list.

My plain advice on choosing an AI code review tool

Run two or three tools on the same pull requests for a fortnight and count the comments your team found useful. The best fit is the one whose suggestions people act on, not the one that leaves the most comments.

Write your coding rules down before you start, because most reviewers can follow them once they're written. For checks that run before review, my article on AI-driven static analysis tools explains how they fit together.

Frequently asked questions

What is an AI code review tool?

An AI code review tool reads pull requests and comments on bugs, risky changes, security issues and style, before a human reviewer approves the change.

Are AI code review tools free?

Some have free plans for single developers or open source projects, and others offer trials. The free plan column above shows what each vendor's site says.

Can AI replace human code review?

Not fully. It catches many common problems quickly, but people still need to judge design, logic and business rules.

Is my code safe with an AI reviewer?

Check each provider's policy on storing code and training models, and consider self-hosted options for sensitive projects.

Do AI code reviewers work with GitLab and Bitbucket?

Many support GitHub, and several also work with GitLab and Bitbucket. Check the integrations each one lists.

Can an AI reviewer follow my team's coding standards?

Many let you add custom rules or instructions so reviews reflect how your team writes code.