AI Receptionist Implementation Notes: Intent, Rules, Handoff

An AI receptionist should be designed like an intake system, not a novelty voice demo.

The minimum architecture has three layers:

1. Intent capture — booking, quote, cancellation, urgent issue, routine question, or general message.
2. Business rules — what the system may answer, what it must collect, and what it must escalate.
3. Handoff output — a short summary that lets a human act without replaying a long voicemail.

{
  "caller": {"name": "", "phone": ""},
  "intent": "booking | quote | callback | urgent | general",
  "context": "what the caller needs",
  "urgency": "low | normal | high",
  "allowed_next_step": "answer | collect_details | escalate | call_back",
  "handoff_owner": "front_desk | sales | operations",
  "summary": "one paragraph the team can use"
}

Guardrails to build before launch

• Do not let the assistant invent prices, availability, policies, or regulated advice.
• Keep the first workflow narrow: missed calls, overflow, or after-hours intake.
• Define escalation paths for angry, urgent, confused, or sensitive callers.
• Review transcripts early and tune unclear questions.
• Measure whether staff receive better summaries, not whether the voice sounds impressive.

Test cases worth running

• A normal appointment request.
• A price shopper.
• A caller who changes their mind mid-call.
• An urgent request that should be escalated.
• An after-hours caller who needs reassurance.
• A caller asking for something outside policy.

Canonical VoiceFleet guide: https://voicefleet.ai/us/blog/ai-receptionist