The Top 10 AI Code Review Tools in 2025
One of the things that comes along with today’s AI craze is the explosion of new tools in the market. On one hand, it’s great that there is a ton of competition and so many options for projects, but on the other hand, it can make it hard for us all to keep up. One area most software shops should keep a close eye on is code review tools. At Solution Street we do code reviews on all of our projects, so looking for tools to help with these reviews is something we care about.
Recently a CTO group I belong to (ctolunches.com) had a lively discussion of these tools, whether or not they were useful and which were best. The general consensus among CTOs was that several of these tools are very useful, but most CTOs think they should not replace human reviewers.
Here is a summary of the CTO group discussion. The list presents the top 10 AI code review tools (ranked by most number of recommendations) that folks are using, along with some key takeaways:
Top 10 AI Code Review Tools
| # | Tool | Notes | Estimated Cost |
| 1 | Code Rabbit | Helpful suggestions in PRs: Positive comments on the suggestions it provides in PRs, calling them “often good catches & good learning opportunities for newer developers.” Reduced “little stuff” in reviews: It was stated that CodeRabbit helped “reduce the ‘little’ stuff that the senior devs used to catch in their review.” Customizable personality: It was noted that giving CodeRabbit a personality led to “amusing quips.” Learning and adaptability: It was observed that CodeRabbit “seems to learn well from devs telling it what is and isn’t a bug,” providing an example where it learned not to flag zips stored as ints when an external provider forced it. Assistance with documentation/ understanding changes: It was highlighted that CodeRabbit “does a good job of providing a stab at creating mermaid diagrams and an overview of what the changes are in each file,” which “helps other human code reviewers be more effective.” | $12-$24/month/seat |
| 2 | Greptile | Reasonably priced and worth it for smaller scale projects for sure! | $30/month/seat |
| 3 | BugBot (from the Cursor team) | Some found it useful for surfacing “possible bugs, misconfigurations” and noted developers complained when it was disconnected. | $40/month/seat |
| 4 | Github Copilot Review | Mentioned that it paid for itself on the first 5-10 pull requests! | Included in paid versions ($10/month/seat for Copilot Individual) |
| 5 | Sourcery.ai | One CTO found it “incredibly accurate” and had a significant impact. Also the pull request descriptions were excellent! | $12-$24/month/seat |
| 6 | Gemini Code Assist | It was mentioned it was worth the money for sure! | Free/$19-$54/month/seat |
| 7 | CodeSherlock.ai | Relatively newer tool; does PR reviews and Code editor code analysis both with one GitHub account; has one of the most comprehensive code analyses in code editors and a powerful critical analysis in PR reviews. Cuts the PR reviews turnaround time significantly. | Free-$15/user/month |
| 8 | Codex (with ChatGPT) | Seems to only work with GitHub, but brings the power of ChatGPT to code analysis and reviews. It is agentic, so you can kick off multiple tasks at once. | Included in gptplus |
| 9 | Cline + Ollama | Great if you want to keep everything local; you can run your own LLM and analyze your source without the traditional privacy worries. | Open source for now |
| 10 | All-hands.dev | Also allows you to run with local model or use credits from another model. | Credit based |
I hope you found this list of tools and comments from my fellow CTOs helpful. Summarizing the response from the group, it seems there are many great choices. Code Rabbit stands out as the one that was given the most positive feedback. For folks with high privacy demands, Cline + Ollama and All-hands.dev offer options where you can use your own in-house run LLM, keeping your data inside your castle walls!
At Solution Street, we are actively using several of these and have found them to be a solid productivity boost when used properly. We carefully consider the feedback, analyze the tools and make our own decisions versus blindly trusting them!