# Real-time voice intake pilot

> Pilot a narrow voice intake experience that transcribes intent, routes simple requests, and hands sensitive or uncertain conversations to people.

- Canonical: https://gptnavi.com/workflows/realtime-voice-intake-pilot
- Category: Customer Support
- Difficulty: Advanced
- Setup time: 4 hours
- Estimated time saved: 3-10 hours
- Last materially updated: 2026-08-19
- Best for: Service businesses, Support teams, Product teams
- Tools: LiveKit, Deepgram, AssemblyAI, Hume AI, HubSpot

## Quick answer

Voice AI works best when its job is small: understand a request, collect minimum necessary details, confirm the next step, and escalate when the policy says to stop.

## When to use it

- After-hours intake
- Callback requests
- Appointment routing
- Product voice prototype

## Steps

1. **Set the call policy** — Define disclosure, allowed requests, data-minimization rules, prohibited commitments, escalation triggers, and the human owner. Tool: HubSpot. Expected output: A documented call policy.
2. **Create the real-time session** — Build a low-latency audio session with interruption handling, status signals, and a clean exit to a human route. Tool: LiveKit. Expected output: A testable voice session.
3. **Transcribe and confirm intent** — Use live transcription to identify the request, then have the system confirm what it heard before creating a record. Tool: Deepgram. Expected output: A verified call summary.
4. **Extract only useful fields** — Generate structured intent, urgency, and next-step fields; sample results against recordings before relying on automation. Tool: AssemblyAI. Expected output: A reviewed intake record.
5. **Test the conversation experience** — Review interruption handling, tone, accessibility, and confusion cases, then route uncertainty to a person rather than guessing. Tool: Hume AI. Expected output: An approved pilot experience.

## Prompt templates

### Voice intake script

Write a safe voice intake script for this business. Include greeting, automation disclosure, allowed questions, minimal data collection, confirmation, exceptions, escalation, and closing. Business: [paste]

### Call QA rubric

Create a quality rubric for AI-assisted intake calls. Score disclosure, transcription accuracy, intent capture, data minimization, escalation, tone, customer outcome, and unsupported promises. Calls: [paste]

## Common mistakes

- Using a voice agent for high-stakes advice
- Failing to disclose automation or recording
- Capturing sensitive data that the workflow does not need

## Related workflows

- https://gptnavi.com/workflows/ai-voice-intake-with-human-handoff
- https://gptnavi.com/workflows/customer-onboarding-to-first-value
- https://gptnavi.com/workflows/support-triage-to-product-backlog