AI App Testing for Features That Don't Behave the Same Way Twice
Standard test assertions fail on AI features because outputs are dependent on behavior and intent. mabl can test for exactly that, so your AI-powered features stay reliable as models and prompts evolve.
Accelerate AI innovation by 9x with agentic testing
Validate Semantic Outputs
Define what a correct response means, not what it says or looks like. mabl’s agentic testing evaluates outputs against your criteria using intent-based assertions that survive the natural variation of LLM outputs.
Guardrails and Safety Checks
Validate that AI features respect your defined guardrails, including content policies, response boundaries, and prohibited outputs, consistently across every test run.
End-to-end AI Feature Coverage
mabl authors test flows for AI-powered features, executes them continuously, analyzes outputs against your criteria, and keeps coverage current as your models and prompts evolve. The same coverage that protects your web flows extends naturally to AI touchpoints within those flows.
Natural Language Assertions
Traditional web app assertions check for an exact string. For AI features, that approach breaks immediately. mabl lets you describe what a correct response looks like in natural language, evaluating the actual output against your criteria without requiring an exact match.
Your AI Features Deserve to Be Tested the Way Your Customers Use Them
See how mabl validates non-deterministic behavior and catches AI regressions before they reach your users.
