Test Your AI Before Your Customers Do

Most AI products look good in a demo. They break in the long tail: a caller interrupts, switches languages, gives contradictory details, or takes a path the test script never covered.

Human QA can find some of those failures. It cannot try every conversation, click path, language, and edge case on every release. Static evals have the same limitation. They score individual responses, while customers interact with a product over time.

Toyon tests the product through simulated users. Thousands of agents speak, listen, click, and type their way through it in parallel. They complete normal workflows, branch into unusual ones, and probe likely failure modes based on the product and its industry.

Because the users are simulated, teams can run the same population before a pilot, after a model change, and on every deployment. Each run produces failure rates, transcripts, and reproduction steps. Teams can see where the product breaks, how often it happens, and whether a fix introduced a regression somewhere else.

Toyon is state of the art on the SM-100 benchmark, finding 3.19 times as many bugs as the GPT-5.5 reference agent.

Customers will explore paths your test plan missed. Simulated users let you get there first.