The best code review tool depends on where your code lives and how strict your process is: the review built into your Git host suits most teams, a dedicated review tool suits regulated or very large projects, and an AI reviewer suits teams drowning in pull requests. Eleven options follow in no particular order.
Code review is the step where another person, or now an AI, reads a change before it joins the main codebase. It catches bugs, spreads knowledge around the team and stops one person's bad day becoming everyone's outage.
The eleven tools below are listed alphabetically and in no particular order, from open source review servers to AI reviewers that comment on every pull request. Every description comes from the vendor's own site, read this week. If you're using a chatbot to help review, my AI prompts for code review are a handy starting point.
Code review tools side by side
In the free plan column, Yes means the tool's own site names a free plan, a free version, a free tool or an open source edition. Trial only means a time-limited trial. Not stated means the pages I read named neither, even where there's a button inviting you to try it.
| Tool | Type | Good for | Free plan |
|---|---|---|---|
| Bitbucket | Git hosting with pull requests | Teams already using Jira | Not stated |
| CodeRabbit | AI pull request reviewer | Automatic first-pass review on every PR | Trial only |
| Collaborator | Peer review for code and documents | Regulated industries and audit trails | Not stated |
| DeepSource | Automated code review platform | Automating routine review checks | Trial only |
| Gerrit Code Review | Open source patch-based review | Strict review before anything merges | Yes |
| GitHub | Built-in pull request reviews | Code already hosted on the platform | Not stated |
| Graphite | AI code review platform | Stacked pull requests and fast reviews | Trial only |
| Greptile | AI reviewer with full codebase context | Solo developers and small teams | Yes |
| Qodo | Multi-agent code review | Enforcing team standards on every PR | Yes |
| Review Board | Code, image and document review | Reviewing more than just code | Not stated |
| Reviewable | Review tool for pull requests | Deeper reviews of big pull requests | Not stated |
Eleven code review tools to try
Bitbucket
Best for: Teams already on Jira that want code review, CI/CD and security checks in the same Atlassian product.
CodeRabbit
Best for: Busy teams shipping lots of AI-written code who want every pull request reviewed automatically before a human looks.
Collaborator
Best for: Companies in regulated fields such as automotive, aerospace and healthcare that need reviews of code and documents with compliance records.
DeepSource
Best for: Engineering teams that want routine review checks automated, now that the company has joined Harness, with a free trial.
Gerrit Code Review
Best for: Large or open source projects that want a self-hosted, patchset-based review platform for Git with strict gatekeeping.
GitHub
Best for: Developers whose code already sits in its repositories and want review, comments and checks right where they work.
Graphite
Best for: Fast-moving teams that want AI review plus a smoother pull request flow, with Cursor's cloud agents now built in.
Greptile
Best for: Developers who want an AI reviewer that understands the whole codebase, with a free starter tier for one developer.
Qodo
Best for: Engineering leads who want organisational standards checked on every pull request, free for open source projects.
Review Board
Best for: Projects that review images and documents as well as code and want a long-running, self-hosted review tool.
Reviewable
Best for: Reviewers who find their Git host's built-in review screen too thin for long, multi-round reviews of big pull requests.
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Built-in reviews, dedicated tools or AI reviewers?
Your Git host already has pull requests or merge requests, and for many teams that's enough. Dedicated review tools add things the built-in screens lack, such as patch-by-patch review, review of documents and images, or the audit trails regulated industries need.
AI reviewers are the newest group. They read every change and leave comments in seconds, which helps when people are writing far more code with AI than humans can review. They're a first pass, not a replacement for the person who understands the product.
What the UK code of practice expects
The UK Software Security Code of Practice asks organisations to have a clear process for testing software and software updates before distribution, and to follow secure by design and secure by default principles throughout the development lifecycle.
Review is part of that process. Write down what must be reviewed, by whom, and when a change can merge. A tool can enforce those rules, but it can't decide them for you.
Questions to ask before you choose
- Does it work with the Git host we already use?
- Can we require approvals before a merge?
- How noisy are its AI comments, and can we tune them?
- Does it keep a record of who approved what?
- Can it review documents or designs as well as code?
- Will it slow down small, urgent fixes?
Signs your review process is stuck
- Pull requests wait for days. Reviews need an agreed response time.
- Approvals are rubber stamps. Changes are too big to read.
- The same comments repeat. Automate them with a linter or an AI reviewer.
- One person reviews everything. Spread the knowledge around.
Do you make a code review tool? Tool makers can ask to be considered for a featured place on this list.
My plain advice on code review
Keep pull requests small. No tool rescues the review of a giant change, and small changes get better feedback faster. Use an AI reviewer to catch the obvious things so people can spend their attention on design and logic.
Agree what a good review looks like and write it down: what to check, how fast to respond and when to approve. For the automated checks that should run before anyone reviews, see how AI-driven static analysis helps.
Frequently asked questions
What is a code review tool?
It's software that lets team members read, comment on and approve code changes before they're merged into the main codebase.
Can AI replace human code review?
Not fully. AI reviewers catch common problems quickly, but people still need to judge whether a change makes sense for the product.
Is the review built into a Git host enough?
For many small teams, yes. Dedicated or AI tools help once reviews pile up or you need stricter rules and records.
How many reviewers should approve a change?
One careful reviewer is enough for most changes. Riskier areas, such as payments or security code, often need two.
What is patchset-based review?
It's a style where each change is reviewed as a series of patches that are updated in place until approved, rather than as one growing pull request.
Are there free code review tools?
Yes. Some tools in the table name a free tier or an open source edition on their own site. Check the free plan column.
