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Test how your agent gathers what it needs.

A bad agent asks ten questions in a row like a form wizard. A good agent weaves questions into conversation, doesn't ask for what it already knows, and handles the messy reality of how people actually talk: incomplete addresses, forgotten ZIP codes, self-corrections, "I don't know" answers, and answers that change mid-sentence. Coval tests whether your agent collects the right information without making callers feel interrogated.

Test Information Collection on Your Agent

What we check.

We score each transcript against the collection rules for your context:

  • Collects only the fields it needs for the request.
  • Asks in a conversational flow rather than a checklist.
  • Handles partial answers, corrections, and refusals without getting stuck.
  • Works with approximate information when the caller doesn't have exact details.
  • Doesn't ask for SSN to schedule an AC repair.

We also run the edge cases that derail collection: callers who give an address in pieces, change their answer mid-sentence, refuse to share insurance info, mention a second issue mid-call, or genuinely don't know what they need.

How it works.

Tell Coval what your agent does. We use vertical defaults to know what fields matter, generate collection scenarios that include messy real-world inputs, and check whether the agent gathered what it needed without acting like a form, and if you want to test for specific fields, add them and we'll calibrate to your exact requirements.

What you'll catch.

  • Agents that capture the wrong phone number and the callback fails.
  • Agents that miss the allergy and the order is dangerous.
  • Agents that confirm 123 Main Street when the caller corrected to 132.
  • Agents that refuse to schedule because the caller doesn't have their insurance card handy.
  • Agents that ignore the secondary symptom the caller mentioned in passing.

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