Key takeaways
- A large language model reads or listens to every call and answers the same fixed questions: what the customer wanted, what happened, and whether the issue was resolved.
- Calls marked unresolved go straight to a daily follow-up list, so an open issue gets a callback before the customer calls again or cancels.
- Your quality team checks a sample of summaries against the recordings and tunes the prompt until the flags match their own judgment.
- The summaries and recordings run in your own environment, and PII redaction can remove personal data before a model ever sees it.
Know what every caller wanted, not just the ones you sampled
Your contact center records thousands of conversations a day. Supervisors and quality teams listen to a small sample, and agents write their own wrap-up notes at the end of a busy shift.
That leaves two gaps. You do not know, call by call, what the customer wanted and whether they left with an answer. And the customers most likely to leave are the ones whose issue stayed open, which you find out about only when they call again or cancel.