VAPI + GoHighLevel Integration: The Complete Setup Guide

What this integration does

VAPI handles the AI calling infrastructure (LLM, voice, telephony orchestration). GoHighLevel handles the CRM, pipelines, and downstream automation.

Together: leads enter GHL → trigger VAPI calls → call outcomes flow back to GHL → workflows handle next steps.

The integration isn't pre-built. You wire it up via webhooks and API calls. Here's how.

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Prerequisites

• VAPI account (vapi.ai) — create one
• GoHighLevel account with API access
• Twilio account (VAPI uses Twilio for telephony in most setups)
• Phone number (purchased via Twilio or directly through VAPI)

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Step 1: Provision a phone number in VAPI

VAPI dashboard → Phone Numbers → Add Number.

Two options:

Option A: Buy through VAPI — they provision via Twilio under the hood. Simplest.

Option B: Bring your own Twilio number — if you already have a Twilio account, link it. More control.

For a fresh setup: Option A. ~$1.15/month for a US local number.

Important: the number must be A2P 10DLC registered if you're calling US numbers. Without registration, calls get carrier-filtered.

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Step 2: Build your VAPI assistant

Dashboard → Assistants → Create New.

Configuration:

• Model: GPT-4o-mini (cheaper) or GPT-4o (better quality, higher cost)
• Voice: ElevenLabs voice (natural-sounding) or Cartesia (cheaper, fast)
• First Message: what the AI says when the call connects
• System Prompt: the persona, objective, and behavior rules
• Functions: webhooks the AI can call mid-conversation (e.g., to book an appointment)

A basic system prompt for outbound qualification:

You are Sarah, a friendly AI assistant calling from [Company Name] regarding their solar inquiry. Your goal is to confirm interest, qualify (own home? roof condition? avg utility bill?), and book an appointment.

Guidelines:
- Keep responses under 2 sentences when possible
- If they're not the homeowner, politely end the call
- If they're interested, offer two appointment time options
- If asked "are you a robot?", say "Yes, I'm an AI assistant — would you prefer to speak with a human?"

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Step 3: Set up the GHL outbound trigger

In GoHighLevel, create a workflow:

1. Trigger: "Contact Created" with filter "Tag is X" or "Source is Y"
2. Action: "Send Webhook" — send to VAPI's API endpoint to initiate a call

VAPI's outbound call endpoint:

POST https://api.vapi.ai/call
Authorization: Bearer YOUR_VAPI_API_KEY
Content-Type: application/json

{
  "phoneNumberId": "your-phone-number-id-from-vapi",
  "assistantId": "your-assistant-id",
  "customer": {
    "number": "+15551234567",
    "name": "{{contact.first_name}}"
  }
}

GHL's webhook action lets you map contact fields to the request body.

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Step 4: Configure VAPI webhook to GHL

You want call outcomes back in GHL.

In VAPI dashboard → Assistant settings → Server URL.

Set to a webhook endpoint that processes VAPI's call events. Two options:

Option A: VAPI → GHL directly — GHL workflow with "Inbound Webhook" trigger receives VAPI events.

Option B: VAPI → Make.com → GHL — Make.com middleware for transformation/logic before updating GHL.

Option B is more flexible. Recommended for production use.

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Step 5: Make.com middleware (recommended)

Create a Make.com scenario:

1. Webhook trigger: receives VAPI events
2. Router: branch on message.type:
   • end-of-call-report → process call outcome
   • tool-call → handle function calls (e.g., AI wants to book an appointment)
3. For end-of-call-report:
   • Extract call data (transcript, duration, summary, structured data)
   • Determine outcome (appointment booked, qualified-no-book, not-interested, no-answer)
   • Look up contact in GHL by phone number
   • Update contact custom fields with call data
   • Move opportunity to appropriate stage based on outcome
   • Trigger downstream GHL workflow (e.g., send confirmation email if booked)

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Step 6: Function calls (the AI taking actions)

VAPI's killer feature: the AI can call functions mid-conversation to do things.

Example: "Book this appointment"

In your VAPI assistant config, define a function:

{
  "name": "book_appointment",
  "description": "Book an appointment for the prospect at the agreed time",
  "parameters": {
    "type": "object",
    "properties": {
      "datetime": {"type": "string", "description": "ISO 8601 datetime"},
      "duration_minutes": {"type": "number"},
      "notes": {"type": "string"}
    },
    "required": ["datetime"]
  }
}

When the AI determines it should book an appointment, it calls this function. VAPI fires a webhook to your server with the parameters.

Your Make.com scenario:

1. Receives the function call
2. Calls GHL's calendar API to create the appointment
3. Returns a response to VAPI ("appointment booked for Tuesday 3pm")
4. The AI confirms with the prospect: "I've booked you for Tuesday at 3pm. You'll get a confirmation email shortly."

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Common gotchas

1. Webhook payload format mismatch

VAPI's event payloads have a specific structure. Your Make.com mapping must match exactly. Test with real call data before going live.

2. Phone number format mismatch

VAPI expects E.164 (+15551234567). GHL's phone field might store other formats. Normalize before sending to VAPI.

3. Call queuing limits

VAPI has concurrent call limits (varies by plan). If you trigger 1,000 calls in a minute, most will fail. Throttle outbound triggers.

4. Latency

VAPI calls take 30-90 seconds to initiate. Don't expect instant. Build async workflows that don't block on the call result.

5. Cost surprises

Calls at $0.05-$0.15/minute add up. Set budget alerts. Monitor cost daily during early deployment.

6. Compliance

US calls require TCPA-compliant consent. Ensure your form captures explicit consent for AI calls. Calling without consent = legal risk.

7. Time zone handling

If your prompt says "are you available tomorrow at 3pm?", which time zone? Pass timezone in the call context. Have the AI confirm time zone explicitly.

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Cost breakdown

For 100 outbound calls/day:

• VAPI fees: ~$0.05-$0.10/minute average call (3-5 min calls = $0.15-$0.50/call)
• Twilio: ~$0.013/minute outbound + ~$1.15/month per number
• GPT-4o-mini: ~$0.005/call
• ElevenLabs voice: ~$0.05-$0.10/call
• Make.com operations: ~10 ops/call

Daily: 100 calls × $0.30-$0.60/call = $30-$60/day = $900-$1,800/month.

For comparison: 1 human caller at $20/hour × 8 hours/day × 22 days = $3,520/month for 50% the call volume. The AI is meaningfully cheaper at scale.

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Testing protocol

Before going live with real prospects:

1. Test with your own phone number (10-20 test calls)
2. Verify each call outcome routes correctly to GHL
3. Test edge cases: no-answer, voicemail, hang-up early, hostile responses
4. Verify GHL pipeline movement matches expected outcomes
5. Test function calls (appointment booking, transfer to human)
6. Run a 50-call pilot with a small list before scaling to thousands

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Going live

Phase 1 (Day 1-7): 50-100 calls/day, monitor every call for issues.

Phase 2 (Week 2-4): 200-500 calls/day, refine prompt based on transcripts.

Phase 3 (Month 2+): scale based on performance metrics.

Don't go from 0 to 1,000/day in week one. Issues compound at scale.

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Sources

VAPI features and pricing from vapi.ai documentation as of April 2026. GoHighLevel API documentation from highlevel.stoplight.io. Twilio pricing from twilio.com/pricing. TCPA compliance is a real legal requirement (47 U.S. Code § 227); consult counsel for specific use cases.

Want help wiring up your VAPI + GHL integration? Let's talk — typical setup is 2-4 days for a single assistant.