See what Axon AI can do across a real release.
Start with the full workflow, from a changed requirement to connected tests, runs, failures, tracker updates, and release evidence. Then go deeper into each QA practice.
Run the Checkout test on Chrome and Firefox and tell me when it is done.
Done. Chrome passed 11 of 11. Firefox passed 10 of 11, and one step self-healed after a button moved. Nothing looks broken from the dev changes. Want the report?
The library
21 guides, no fluff
Each one is a working playbook you can apply this sprint, whether you test by hand or with AxonQA.
Inside AxonQA
These practices, built into the product
The guides describe how we think about test quality. The product runs on the same ideas: tests grounded in your real requirements and flows, self-healing that escalates from quick certainty to careful AI review, and health metrics that make flakiness impossible to ignore.
- Healing escalates, cheapest and most certain checks first.
- The AI is a last resort, and it tells a changed app apart from a broken one.
- Every fix is recorded with its reasoning, and is reviewable and reversible.
Same run, two very different causes.
The app changed, the test did not need to. Fixed during the run, and reversible.
The expected total did not match. Left red with evidence for review.
Cheap, certain checks run before anything expensive, and no fix ever rewrites what your test expects.
Get the next guide when it lands
We write about what actually works in AI-assisted testing, roughly monthly. No noise, unsubscribe anytime.
Your email, nothing else. We never share it.
Put these practices to work
Generate structured test cases from your stories, then validate them with real runs on your own app.