AI Code Review, QA and Test Agents

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.

Products in this category

  • Brass dots linked by thread beside a small gear and an index card, standing for code checked against standards.
    Code Quality

    AI Code Review Agent

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

    From $3,900 Delivery in 20–30 working days
  • A bucket of paper scrolls with one unrolled and pinned by brass tacks, showing Bitbucket code lines flagged for review.
    Code Quality

    AI Code Review Agent for Bitbucket

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

    From $4,400 Delivery in 20–30 working days
  • A paper strip with brass pins marking spots beside a green pencil, showing lines flagged in a GitHub pull request.
    Code Quality

    AI Code Review Agent for GitHub

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

    From $4,400 Delivery in 20–30 working days
  • Two paper strips joined under a brass ring with a stone marker, showing a GitLab merge request reviewed before merging.
    Code Quality

    AI Code Review Agent for GitLab

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

    From $4,400 Delivery in 20–30 working days
  • Coiled chain link, an open wooden box and a small gear seen from above, standing for tested dependency upgrades.
    Code Quality

    AI Dependency Update Agent

    Proposes and tests dependency upgrades as reviewable pull requests.

    From $1,900 Delivery in 20–30 working days
  • Small signal tower, empty window frame and slider control arranged diagonally, standing for tests run and results reported.
    Code Quality

    AI QA Agent

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

    From $3,900 Delivery in 20–30 working days
  • A brass bracket sculpture around an empty window frame with a green toggle, standing for tests run on each code change.
    Code Quality

    AI QA Agent for GitHub

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

    From $4,400 Delivery in 20–30 working days
  • Stacked layered boxes with a brass slider and a green notebook, standing for tests run at each pipeline stage and logged.
    Code Quality

    AI QA Agent for GitLab

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

    From $4,400 Delivery in 20–30 working days
  • Chain links, a small box and a signal tower in a three-quarter still life, standing for new tests linked to existing code.
    Code Quality

    AI Test Generation

    Generates unit and integration tests for existing code.

    From $2,900 Delivery in 20–30 working days

Where do these agents help an engineering team?

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.

  • Inline review comments on bugs, security and standards
  • Generated unit and integration tests for existing code
  • Structured test plans with defects reported alongside evidence
  • Dependency upgrades proposed as reviewable pull requests

Which product should you pick?

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.

Questions buyers ask

Does the review agent merge code on its own?

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.

What if our code is on a platform other than GitHub?

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.

How is the AI QA Agent different from AI Test Generation?

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.

Choosing between Code Quality products?

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.

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