
AI Code Review Agent
Reviews pull requests for bugs, security issues and standards and comments inline.
Good engineering teams still miss things when the review queue is long and the test suite is thin. These AI systems take on the careful, repetitive side of code quality. They review pull requests, write tests, run test plans and propose dependency upgrades, so your developers can spend their attention on design and the tricky bugs.

Reviews pull requests for bugs, security issues and standards and comments inline.

Reviews pull requests for bugs, security issues and standards and comments inline, connected natively to Bitbucket so it reads and updates repositories,…

Reviews pull requests for bugs, security issues and standards and comments inline, connected natively to GitHub so it reads and updates repositories,…

Reviews pull requests for bugs, security issues and standards and comments inline, connected natively to GitLab so it reads and updates projects,…

Proposes and tests dependency upgrades as reviewable pull requests.

Runs structured test plans against your application and reports defects with evidence.

Runs structured test plans against your application and reports defects with evidence, connected natively to GitHub so it reads and updates repositories,…

Runs structured test plans against your application and reports defects with evidence, connected natively to GitLab so it reads and updates projects,…

Each product targets a step that tends to get rushed. Reviews get skimmed when a release is close. Tests get skipped for older code nobody wants to touch. Dependency updates sit for months because testing them is tedious. These agents do the first pass on that work and hand it back as comments, defects or pull requests that a person can review.
If review is the bottleneck, start with the AI Code Review Agent. If coverage is the worry, AI Test Generation writes tests for code you already have. The AI QA Agent runs test plans against your application and reports defects with evidence. The AI Dependency Update Agent keeps libraries current without a weekend of manual testing.
The code review agent comes in GitHub, GitLab and Bitbucket editions, and the QA agent in GitHub and GitLab editions. Pick the edition that matches where your code lives so the agent works with your pull requests, merge requests and pipelines directly. If your team uses another platform, the core products are the place to look.
No. The AI Code Review Agent comments inline on pull requests, much like a careful colleague would. Your developers read the comments and decide what to change. The AI Dependency Update Agent works the same way and opens reviewable pull requests rather than pushing upgrades straight into your main branch.
There are native editions for GitLab and Bitbucket as well. The code review agent covers all three, and the QA agent has GitHub and GitLab versions. The core products are also available if you use something else. Check the Scope Card to see exactly which connections are included.
AI Test Generation writes unit and integration tests into your codebase. The AI QA Agent works from the outside, running structured test plans against your application and reporting defects with evidence. One improves coverage in the code itself, and the other checks how the running product behaves. Some teams use both.
Tick Compare on up to four products to see scope, price and delivery side by side. If you would rather talk it through, an expert can help you pick the one that fits how you work.