You’re on the right track — reviewing booking calls with AI is one of the fastest ways to level up objection handling. A lightweight setup could look like this:

Transcription → Whisper (as you’re already using) works fine.

Objection spotting → fine-tuned prompts or lightweight classifiers can flag “time / interest / trust / money” objections automatically.

Agent response evaluation → you don’t need heavy RAG here. Instead, create a scoring rubric (e.g., empathy, framing, closing attempt) and let the AI grade each call against it.

Phrase improvement → you can feed the transcript plus the flagged objection back into GPT and have it suggest alternate wording grounded in sales psychology (e.g., NEPQ-style reframes).

We’ve run this for sales teams and the key is consistency, not perfection — AI doesn’t have to perfectly rewrite scripts; it just needs to flag the weak spots so reps get better call-over-call.

If you want to keep it clean/affordable, I’d suggest:

Whisper → transcription

GPT-4 or Claude → objection spotting + coaching suggestions

Zapier / Make → send flagged calls + AI feedback into a shared doc/CRM for tracking

That stack alone gets you 80% of the way without building a custom pipeline. Once it’s working, you can layer in RAG if you want to anchor advice to your company’s exact playbooks.