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Build reliable AI agents that you can trust at scale

Testing and evaluation tools to validate agent behavior, spot risks, and optimize performance

Decagon’s integrated testing suite helps teams validate agent behavior before deploying to production and for every subsequent logic update.

With built-in unit tests, integration checks, and scalable simulations, you’ll catch hallucinations, logic breaks, and tone mismatches early, so your agents stay reliable, on-brand, and customer-ready.

Validate agent behavior before reaching production

Unit testing

Write tests to verify that agents respond accurately, follow policies, and reflect your brand tone, ensuring every response meets your company’s standards.

Integration checks

Confirm that your agent reliably triggers the right actions, uses correct data and tools, and follows business logic, even in your most complex workflows.

Evaluation model rationale

Double-click to inspect the evaluation model’s rationale and see exactly why a test passed or failed

Maintain consistency throughout the agent lifecycle

Scalable simulations

Automatically generate conversations modeled on your customer personas and evaluate agent performance across realistic tones, intents, and scenarios.

Real-time agent previews

Quickly simulate conversations to see exactly how an AOP behaves across different paths, inputs, or edge cases— so you can spot and fix issues with fast feedback.

Scheduled testing runs

Set up recurring simulations that automatically validate behavior over time, so you can continuously monitor changes and catch issues before they impact customers.

Ensure high performance at enterprise scale

Omnichannel support

Model full-length, multi-step interactions like billing disputes, order returns, or reservation bookings to ensure agents handle real-world scenarios across both Chat and Voice.

Observability and tracing

Trace and audit every decision an agent makes step-by-step. With full transparency into the AOP execution path, you can pinpoint and resolve issues faster.

Automated alerting

Trigger alerts to tools like PagerDuty when key performance metrics fall outside defined ranges, so teams can respond quickly before customers are impacted.