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Four simple steps to robust AI agents.
Import your Agent via SDK or API endpoint.
Design test scenarios with visual builder.
Run benchmarks & adversarial simulators.
Get deep insights on accuracy & safety.
Empower your QA team to build complex, multi-turn conversation scenarios without writing a single line of code. Drag, drop, and configure logic nodes to test edge cases.
@monitor
def chat_agent(msg):
# PII Masking: Auto
return agent.process(msg)Don't just test with static datasets. Pit your agent against aggressive 'User Simulator' bots designed to break your guardrails, inject PII, and trigger toxic responses.
@monitor
def chat_agent(msg):
# PII Masking: Auto
return agent.process(msg)Trace every chain of thought. Integration with Langfuse allows you to inspect tokens, latency, and cost per interaction. Debug failures at the step level.
@monitor
def chat_agent(msg):
# PII Masking: Auto
return agent.process(msg)See how leading companies secure their AI agents.
"LangEval cut our red-teaming time by 80%. The automated attack bots found edge cases we never thought of."
"The visual builder allowed our product managers to design complex test scenarios without bugging the engineering team."
"Finally, a way to trace token costs and latency per step. Essential for our production monitoring."