Mabl is a low-code test automation platform where AI creates, maintains and diagnoses end-to-end tests for web applications.
Mabl lets teams build reliable UI tests without heavy scripting. Tests are created through a recorder, and Mabl’s AI handles the fragile parts: auto-healing selectors when the UI changes, visual anomaly detection and intelligent waits that eliminate flaky results. When tests fail, the platform captures screenshots, logs and network traces and uses AI to suggest root causes. Tests run in the cloud across browsers and integrate into CI/CD pipelines, with dashboards reporting quality trends over time.
Mabl is a subscription platform priced by test volume and users, with a free trial for evaluating the workflow on your own application.
It serves QA and engineering teams that want maintainable end-to-end test coverage without dedicating engineers to test scripting.
Record test flows in the browser while Mabl learns the application’s behavior, then run them in the cloud across browsers and environments. AI auto-heals selectors when the UI changes, flags visual regressions and captures screenshots, logs and network traces on failure. Diagnostics suggest likely root causes, and results surface in dashboards and CI/CD pipelines.
QA teams keep suites healthy by testing user-critical journeys first — login, checkout, core workflow — rather than chasing coverage percentages. Review auto-healing reports periodically to confirm the AI is tracking the right elements. Integrate runs into pull requests so failures block merges while context is fresh, which is when fixes are cheapest.
Mabl is paid with a free trial; production use requires a subscription based on testing needs.
Yes, APIs and CLI tools let teams trigger tests, pull results and integrate Mabl into CI/CD pipelines.
Mabl’s auto-healing and diagnostics dramatically reduce the maintenance burden that makes traditional UI test suites so costly.
Yes, tests trigger through the API and CLI on every build, with results surfaced where developers work. Failures include screenshots, logs and traces so triage happens quickly, and dashboards track quality trends across releases.
Machine-learned locators adapt to UI changes automatically, and visual checks catch rendering regressions early. Maintenance time drops sharply compared with traditional suites where every redesign breaks selectors.