Scaling White-Label AI Voice Receptionists — What Actually Matters?

I’m building a white-label, voice-only AI receptionist for medical and dental offices that agencies can resell under their own brand. It answers patient questions using the clinic’s website (RAG), handles basic appointment intake, clearly transfers callers to a human when needed, and logs every call to a simple CRM.

For those who’ve built or deployed AI voice agents at scale, what practical issues show up in real use (handoffs, knowledge accuracy, caller trust, support load, etc.), and what design decisions actually made these systems reliable across many clients?

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