In 1–2 weeks, a QA Health Check gives you your top 10 quality risks, ranked, and a prioritised roadmap.
A crew of specialised AI agents analyses, designs, automates and validates your tests. A senior QA lead reviews and approves each stage before anything moves forward.
Every story moves through four agent stages, from analysis to release. A human gate after each stage approves the work or sends it back with feedback.
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Vague acceptance criteria and contradictory specs become bugs weeks later, when they are the most expensive to fix.
Most checks run through the UI. Pipelines take hours, flaky tests get ignored, and nobody trusts a red build.
Either everything runs on every release or nothing does. Nobody can say which tests prove that this release works.
Each lead agent coordinates its own sub-agents and hands over one structured artefact. The next stage starts only when a human has approved that artefact.
Finds the defects already sitting in the documentation, before anyone writes a test.
Output: analysis report, risk score, verdict
Turns each acceptance criterion into documented tests on the right layer and reuses what you already have.
Output: test cases in Xray, coverage matrix
Automates the approved tests in your stack and runs them until they are stable. When the product is wrong, it reports a bug instead of bending the test.
Output: pull request with passing tests
Works out what the release changed, selects the regression tests that matter, runs them and explains every failure.
Output: release report, Go/No-Go recommendation
A test pyramid is a ratio, not a drawing. We cover every layer and keep most of the checks where feedback is fastest and cheapest.
Cloud & infrastructure covered where tests need it: AWS Lambda, S3, Secrets Manager, Docker.
In centaur chess, a human working with a machine beats both the strongest player and the strongest engine. Quality engineering works the same way.
| AI testing tool | Traditional QA team | CentaurQA | |
|---|---|---|---|
| Senior judgment on every result | No | Depends on the team | Yes, four approval gates |
| Coverage | Mostly UI | Depends on the team | Requirements to E2E, plus NFR |
| Fits your stack and CI | Its own platform | Yes | Yes, your frameworks and pipelines |
| Commercial model | Licence plus your team's time | Ongoing headcount | Fixed-scope engagements |
Fixed scope, fixed price and clear deliverables. Every engagement starts with a free 30-minute call.
1–2 weeks
4–8 weeks
Monthly
Chatbots and agents fail differently from ordinary software: the same question can get a different answer. They need their own kind of testing, with the same human sign-off.
No. It takes the repetitive work off them: document analysis, drafting tests, automating them and triaging failures. That leaves your people free for judgment and exploratory testing. You can also use CentaurQA to set up the process and then run it yourselves.
That is what the four gates are for. Nothing reaches your backlog, your repository or your release decision without a senior engineer reviewing it. The agents also check their own work against strict quality rules before a human sees it.
For automation work, yes. Our default is to run the agents in your environment, with read-only access wherever possible and no direct commits to protected branches. A Health Check can start from documentation, specs and CI output alone.
Java, Python and TypeScript test stacks; REST, GraphQL, Kafka and database integrations; GitHub Actions, GitLab CI and Jenkins; Jira/Xray for test management. The agents adapt to your existing frameworks and conventions.
Request a Health Check. We start with a free 30-minute call to agree on the scope, and within 1–2 weeks you have a clear picture of your quality risks and a roadmap, whether or not you continue with us.
We start with a free 30-minute call, with no sales pitch. You leave with at least one concrete improvement to your testing.