Release with confidence
The world's most advanced testing harness
The engineering underneath: independent, reliable, resilient.
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Per-task LLM routing
The best model for each testing job. You don't need to worry about upgrades, prompt rewrites, version pinning, or evals.
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Reliable tools for your agent
An MCP for the full testing loop. Broad tool coverage, progressive disclosure, idempotent writes, token-efficient, streaming with keepalive, OAuth.
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Self-healing off a model, not a selector
Every element is modeled as dozens of weighted attributes, so a page change re-identifies it by best overall match, falling back to locating it visually when attributes aren't enough.
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Structural objectivity
An LLM told to make a test pass will edit the DOM or weaken the assertion to get there. mabl runs your deployed app in a real browser, in a separate context, and checks it against assertions you defined separately.
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Your intent, translated
You describe what to test and set your guardrails; mabl's tuned metaprompts turn that into the structured instructions the agent runs on, scoped per agent with mabl's own guardrails winning on conflict. You get an effective agent without prompt-engineering it yourself.
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Deterministic first, LLM when needed
Cheap deterministic locators run first; the model engages only when they fail. More efficiency, lower cost, faster.
All your complex workflows, automated end-to-end
Agentic test generation
Create reliable tests from natural language intent and your agent’s context, validated to work.
Web, API, and mobile testing
Cover all your app surfaces, instead of stitching together tools and frameworks.
Email, file, and database validation
Automate the validation of email workflows, file content, and database accuracy.
Test like real users, at scale
Unlimited parallelization
Execute thousands of tests in the mabl cloud for fast results from large test suites
Visual finds and assertions
Define test actions and assertions with natural language, without relying on DOM content alone.
Trust the signal, remove the noise
Agentic failure analysis
Every failed run returns an explanation with evidence and recommendations, optimized for agent consumption
Agentic auto-healing
Instead of failing, tests adjust to unexpected selector changes and UI shifts while preserving intent.
Test reliability reporting
Understand and track test suite health to eliminate time spent on false alarms.