Agentic QA: AI agents that test every release, with senior review

AI agents generate and maintain end-to-end tests for your critical flows, repair them when the UI changes, and file triaged bug reports. A senior QA engineer reviews every report before it reaches you.

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Agentic QA is software testing carried out by AI agents that work through your product the way a tester would, and that keep the tests up to date as the product changes. At Quick Brains, the agents do the repetitive work of recording flows, writing and repairing tests, and drafting bug reports. A senior QA engineer reviews everything before it reaches your team.

It is the ongoing option within our QA services. If you would rather own a test suite yourself, see QA automation.

What is a QA agent?

A QA agent is an AI model connected to a real browser and a set of tools, and given a goal such as “check that a returning customer can reorder from their order history”. It opens the app, decides what to click and type, compares what it sees with what should happen, and writes down what it did. Unlike a recorded script, it can adapt when a button moves or a label changes, because it is following the goal, not a fixed list of clicks.

That flexibility is also its weakness. A QA agent can misread a page, report a problem that isn’t there, or miss one that is. So we don’t sell autonomous AI testing. We use agents for the work they do well, and keep a person accountable for every result.

Where traditional test automation breaks down

Teams that try test automation without a dedicated QA engineer usually run into the same problems:

The suite rots. Tests are written once. Then the UI is redesigned, dozens of selectors break, and fixing them never makes it into a sprint.
Red builds become normal. Nobody triages failures, so the team learns to ignore them, and the suite stops protecting anything.
Coverage stops at what someone had time to script. New features ship without tests because writing them is always the next sprint’s job.
Bug reports are vague. “Checkout is broken” arrives in Slack with no steps, no browser and no screenshot, and a developer loses an hour reproducing it.

How agentic QA works

Record. Agents work through your critical flows on staging, guided by a test plan we agree with you, and record each step.
Generate. The recordings become Playwright tests in your repository. They are ordinary test code, not AI at runtime, so CI runs are fast, repeatable and cheap.
Run. The suite runs in your CI on every pull request or deployment.
Self-heal. When a test fails, an agent works out why. If the UI changed and the test is out of date (a renamed button, a moved field), it proposes a fix to the test as a pull request. If the product is broken, it drafts a bug report. Telling these two apart is where human review matters most.
Report. A senior QA engineer reproduces the bug, sets the severity and files it in Jira, Linear or GitHub Issues with steps to reproduce, expected and actual results, environment, a video and a Playwright trace.
Explore. On new features, agents also run exploratory sessions, trying unusual inputs, small screens and interrupted flows to find what a scripted test wouldn’t.

Pilot first, then a monthly retainer

We start every agentic QA engagement with a fixed-price pilot of two to three weeks, so you can judge the results before committing.

Week 1: kickoff, access to staging and your tracker, and agreement on the critical flows to cover. Agents are set up and start recording.
Week 2: generated tests run in your CI. The first reviewed bug reports arrive in your tracker.
Week 3: we review what was covered, what was found and what the agents got wrong, and propose a retainer scope.

On the monthly retainer, coverage grows with your product, tests are maintained as the UI changes, and every release is tested and triaged. You get a weekly summary and a monthly coverage review.

What you do: provide a staging environment, test accounts and access to your issue tracker, review test pull requests, and join a 30-minute weekly check-in. What we do: everything else.

What you get

Playwright tests in your repository, generated and maintained by agents and reviewed by a senior engineer
Self-healing test fixes as pull requests, so you can see every change to the suite
Triaged bug reports with steps to reproduce, severity, environment, video and trace
A weekly summary of what was tested and found, and a monthly coverage review
Tests that stay yours if you stop the retainer

Who it’s for

A good fit:

Teams that ship weekly and change their UI often
Teams with no QA engineer, or one who is overloaded
Teams with a test suite that keeps rotting after every redesign
Teams that want bug reports they can act on, not just red builds

Not a good fit:

If you want fully autonomous AI testing with no human review, we don’t offer it, and we don’t recommend it
Products without a staging or preview environment, because we won’t run agents against production customer data
Safety-critical systems that require formally validated test processes

Pricing

We don't publish prices, because scope depends on your product. After a 30-minute call you get a fixed price in writing, before any work starts. No hourly billing.

Book a call for a quote

How the work is structured

Pilot (2–3 weeks)
Fixed scope: your critical flows covered, first bug reports filed.
Monthly retainer
Ongoing test generation, maintenance and triaged bug reports.

What is included in our agentic QA

Agents set up on your staging environment and critical flows
Playwright tests generated, run in your CI and kept up to date
Self-healing test fixes delivered as pull requests you can review
Bug reports with repro steps, severity, environment, video and trace
Senior QA review of every report, plus a weekly summary

Frequently asked questions

Is agentic QA the same as AI test automation?

They overlap. AI test automation usually means using AI to write or repair test scripts. Agentic QA goes further, with agents that also explore the product, decide what to test, triage failures and draft bug reports. In our service, the tests that run in your CI are ordinary Playwright code, so runs are fast, repeatable and cheap.

Can AI agents replace our QA engineer?

Not on their own. Agents are fast at repetitive work, such as recording flows, writing tests and reproducing bugs, but they misread pages and sometimes report problems that aren't there. That's why a senior QA engineer reviews everything. For teams without a QA engineer, agentic QA gives you one, with agents doing the legwork.

How do you stop the agents from reporting bugs that aren't real?

Every report is reproduced and reviewed by a senior QA engineer before it is filed in your tracker. Reports that can't be reproduced, or that describe intended behaviour, are discarded. You only see reports a person has checked.

Do the agents touch production or real customer data?

No. Agents work against your staging or preview environments with test accounts. The only thing we run against production is an optional read-only smoke check of critical pages, agreed with you in advance.

What happens to the tests if we stop the retainer?

They stay in your repository and keep running in your CI as ordinary Playwright tests. You lose the automatic maintenance and the bug triage, but nothing is locked into our tools.

Which AI models do you use, and is our code used for training?

We use commercial models from major providers and pick per task based on how well they perform. We use them under API terms that exclude training on your data, and we document which providers process your data in the data processing agreement.

How does the pilot work?

The pilot is a fixed-price, fixed-scope engagement of two to three weeks. We cover an agreed set of critical flows, run the agents, and file the first bug reports. At the end you get a review of what was covered and found, and a proposal for the retainer. You can stop after the pilot and keep the tests.

Playwright QA automation services
Our QA automation services deliver a Playwright end-to-end test suite that covers your critical user flows and runs in your CI on every pull request. You own the code and the documentation; ongoing maintenance from us is optional.
Custom AI agent development services
Our AI agent development services take one real business workflow, such as support triage, lead qualification or document processing, and build a custom AI agent to run it, with guardrails, human-in-the-loop review and monitoring. A fixed-scope discovery tells you what is feasible and what it costs before any build starts.

Talk to a senior engineer this week

Book a 30-minute call. We will ask about your product and goals, tell you honestly whether we can help, and send a fixed-price proposal within two business days.

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