AI-Powered Testing
Writing tests by hand takes time, and keeping them green takes even more. When your app changes, selectors break, suites turn flaky, and failures pile up faster than anyone can triage them. This pillar puts AI to work across the parts of testing that drain the most effort, so your team spends less time maintaining tests and more time shipping.
Who it’s for#
QA engineers, SDETs, and developers who want broader coverage and lower maintenance without growing the test-writing backlog.
What it does#
- AI Test Generation — Turn requirements and source code into ready-to-run tests, and fill coverage gaps the platform finds for you.
- Self-Healing Tests — Recover broken UI locators automatically so a changed element does not fail the whole run.
- AI Failure Analysis — Get a suggested root cause and remediation for a failed run instead of digging through logs.
- Flakiness Detection — Surface tests that pass and fail without changes so you can quarantine and fix them.
- Synthetic Test Data — Generate realistic data for APIs and apps without exposing real customer records.
Why it matters#
Most of the cost in a test suite shows up after it is written, in maintenance and triage. By generating tests, healing broken locators, explaining failures, and flagging unreliable cases, the platform keeps your suite useful as your product moves, and keeps a failing test meaning something.