[multiverse]

Your agent works.
Until it doesn't.

Same code, same prompt - but it fails on the fifth try. Multiverse runs your agent against diverse scenarios so you know where it breaks down before your users find out.

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Multiverse dashboard showing test results with execution flow visualization and scenario outcomes
Trace replay showing a simulated user conversation with tool calls and world state
Features

Agents are unpredictable

You tested it five times and it worked. But will it work on the sixth? Run 50 scenarios and find out.

Scenario generation

Diverse inputs your agent will see in production. Different users, edge cases, failure modes - the variety that manual testing can't cover.

Tool simulation

Every tool call returns consistent simulated data. No real APIs, no test accounts - just your agent running against a realistic world.

User simulation

Persona-driven multi-turn dialogue. Cooperative, impatient, confused, adversarial - each with realistic behavior and guardrails.

Outcome verification

Programmatic checks on what actually happened, not what the agent said it did. Across every scenario, not just the ones you tested by hand.

Live

Watch it run

See where your agent holds up and where it falls apart.

Live view of Multiverse tests running with real-time pass/fail outcomes
Developer experience

Define success,
see the pass rate

Describe your agent, define what "worked" means, and run it across generated scenarios. Get a pass rate, not a single thumbs up.

eval.test.ts
const test = multiverse.describe({
name: 'flight-booking-agent',
task: 'Book flights for passengers',
agent: runMyAgent,
conversational: true,
});
 
const results = await test.run({
success: (world) => {
return world.getCollection('bookings').size > 0;
},
trialsPerScenario: 5,
});

Ship your agent with confidence

Know how it behaves before your users do.

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