Test whether your conversational AI agent still honors the commitments you defined for it, before the next release ships.
Instructions, context, or guardrails were updated.
A new model or version now interprets those instructions.
Tools, routing, or surrounding product logic evolved.
The commitments did not.
Reply rate will not catch it. A missing disclosure, a forbidden claim, or a question asked twice can all look like a successful conversation.
DoppelGegner tests your agent against its playbook and shows the conversation evidence behind each result.
Illustrative example. Not a stored production result.
“Before we continue, could you confirm your notice period?”
The recipient had already answered this in message 4. That turn lost context and lowered the contextual-understanding assessment.
“Before we go further, could you confirm your current notice period?”
The recipient answered in message 4 — “I'm on a 30-day notice.” The agent re-asked without acknowledging the answer.
“Your attachment was rejected — file must be PDF.”
System-voiced error text was sent to the recipient instead of being handled internally.
Deterministic checks run before any model. If a rule fails, no model verdict can override it.
Every finding cites its message and quotes the text. Without both, it does not ship.
Your agent runs on its own platform. We reach it from outside, through a test channel, and evaluate what comes back.
Monitoring tells you what happened. We run before the send.
