Every missed call at a hotel front desk is revenue leaking onto the floor. For our client in Lagos, network reception and staff fatigue meant 30% of booking inquiries were going to voicemail. We fixed it with AI.
1. The Tech Stack
We ignored the standard "Western" SaaS tools and built a custom stack designed for latency-tolerance and accent recognition.
- Voice Layer: Vapi.ai (optimized for low latency).
- Orchestration: n8n (Self-hosted on DigitalOcean).
- Telephony: Twilio (Elastic SIP Trunking).
- Database: Supabase (Real-time booking sync).
2. Solving the "Accent Gap"
Standard out-of-the-box models struggle with nuanced Nigerian English. We fine-tuned the prompt system to recognize local phrasing ("How far?", "I dey come") and mapped them to intent triggers.
// Intent Mapping Logic
{
"keywords": ["price", "how much", "rate"],
"intent": "INQUIRY_PRICING",
"response_style": "localized_professional",
"voice_id": "elevenlabs_custom_lagos_v2"
}
3. The Result: 24/7 Uptime
The AI Agent now handles 100% of Level 1 calls. It checks room availability in real-time via the n8n webhook connection to Google Sheets/Supabase, confirms the price, and sends a payment link via SMS instantly.
| Metric | Before AI | After AI |
|---|---|---|
| Missed Calls | 32% | 0% |
| Booking Time | 8 mins | 2 mins |
| Cost Per Month | $400 (Salary) | $45 (API Usage) |
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