How can an AI-built pricing calculator be improved to better reflect client-specific nuances?

The suggestion offered was to feed the calculator the transcript of the actual diagnostic/discovery call in addition to the structured inputs. The reasoning: discovery calls contain a lot of nuance and detail ("gems" or "gold nuggets") that a dropdown-based calculator can't capture, and including that transcript could help the tool price more precisely for that specific client. This was noted as an enhancement rather than a fix to an existing problem — the calculator's first real-world test resulted in the client saying yes very quickly, which the group interpreted as a sign the price may have been set too low.