Converra generates synthetic test personas from your real conversation data. Each persona carries the intents, behaviors, and edge cases of a real user segment. Scenarios are built from your actual failure patterns. Your test coverage grows as your agent faces new situations.
Most teams test agents with a handful of scenarios they wrote when the agent launched. Those scenarios reflect the happy path, the obvious cases, the things you thought of on day one.
Production tells a different story. Users are confused, impatient, adversarial, and creative in ways no one predicted. The gap between your test cases and your real users is where agent failures live.
Converra identifies behavioral clusters in your conversation data and generates typed personas for each one. Here are examples of what these look like.
Asks vague questions, provides incomplete information, needs guidance through multi-step flows. Tests whether your agent can lead a conversation, or just answer what's asked.
Has context from previous interactions. Expects the agent to pick up where they left off. Gets frustrated with repeated questions. Tests conversation continuity and efficiency.
Knows the product deeply. Pushes boundaries with unusual requests, compound questions, and rapid topic switches. Tests whether your agent handles complexity or collapses to generic responses.
Tries to go off-topic, extract information outside the agent's scope, or push past guardrails. Tests safety and boundary enforcement without compromising helpfulness.
These are examples. Your personas are generated from your data and specific to your product and users.
Real conversations contain clusters: user types that show up repeatedly with similar intents, frustration levels, and communication styles. Converra identifies these clusters from your trace data.
Each persona captures a distinct user archetype: their typical intents, how they phrase things, their patience level, whether they provide information upfront or need prompting. These are specific to your product and users.
Converra generates test scenarios from the conversations where your agent struggled. If your agent fails at upselling during support calls, the test scenario will put the persona in exactly that situation.
When new failure patterns appear in production, Converra generates new personas and scenarios to cover them. Your test coverage grows as your agent faces new situations.
The test scenarios you wrote three months ago reflect how users behaved three months ago. Your product has changed. Your user base has grown. New edge cases have appeared. Manual test suites can't keep up.
When people write test cases, they tend to test what the agent should do well. The failures that matter come from unexpected combinations, odd phrasing, and multi-turn confusion loops. Synthetic personas reproduce these systematically.
A list of input/output pairs doesn't test whether your agent can hold a conversation. Can it recover from a misunderstanding? Can it handle a topic switch mid-conversation? Multi-turn simulation catches what single-turn evals miss.
Every new customer segment, product feature, and failure pattern generates new test coverage. You don't need to write or maintain test cases. The test suite evolves with your product.
Converra combines personas with scenarios to run full multi-turn simulated conversations. Every prompt variant is tested against the same set of personas and scenarios, making comparisons direct and fair. When a variant wins, it has been tested against the same edge cases, the same difficult users, and the same failure patterns as your current production prompt.
Learn about simulation testingPersonas are derived from patterns in your production conversations. They capture user archetypes, intents, and behaviors. No real customer data is used directly in simulations. The personas represent behavioral clusters, not individual users.
It depends on your conversation data. Converra typically identifies 4-8 distinct persona types per agent, each with multiple scenario variants. The count grows as new behavioral patterns emerge in production.
Yes. You can define personas manually for specific test cases you care about, and Converra will include them alongside the auto-generated ones in every simulation run.
A persona defines who the user is (their behavior, patience, expertise level). A scenario defines the situation (what they're trying to accomplish, what context they have, what complications arise). Converra combines personas with scenarios to create realistic multi-turn conversations.
Converra can generate useful personas from as few as 20-30 conversations. More data produces more specific and diverse persona types. You can also start with custom personas and let the auto-generated ones build up over time.
Synthetic conversations follow the same conversational dynamics as your real users: multi-turn exchanges, follow-ups, confusion, topic changes. The difference is that they're targeted at your failure modes and can be reproduced exactly for comparison testing.
Connect your agent and Converra will generate personas from your production conversations. See who your users really are and how your agent handles each type.
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