Overview
WhatsApp voice message integration enables workers to submit grievances by recording voice messages on their phones - no typing required, works with basic smartphones, and leverages a platform workers already use daily. Messages are automatically transcribed, translated if needed, and processed into structured grievance records.
Why WhatsApp Voice?
Accessibility: Workers with limited literacy can speak their concerns naturally.
Familiarity: No new app to learn - uses existing WhatsApp.
Async: Workers can record when convenient, not limited to call center hours.
Evidence: Original voice recording preserved for sensitive cases.
User Journey
1. Initiate
Worker messages the GrieVoice WhatsApp number
2. Record
Sends voice message describing their concern
3. Process
System transcribes, translates, extracts fields
4. Confirm
Receives confirmation with case reference number
Technical Flow
Message Reception Twilio WhatsApp API
Worker sends voice message to WhatsApp Business number. Twilio webhook triggers with message metadata and audio URL.
Audio Retrieval Twilio Media
Server fetches audio file from Twilio's secure media storage. Supports .ogg format (WhatsApp default).
Transcription OpenAI Whisper / Deepgram
Audio converted to text with automatic language detection. Supports Portuguese, English, Swahili, and other languages.
Translation (if needed) GPT-3.5 / Gemini
Non-English transcripts translated while preserving original. Both versions stored for reference.
Field Extraction Claude Sonnet
AI extracts structured fields: name, contact, location, people involved, category, description, urgency.
Storage Supabase
Structured data saved to grievances table. Original audio stored in secure bucket. Source marked as "whatsapp_voice".
Confirmation Twilio WhatsApp API
Auto-reply sent to worker: "Thank you. Your concern has been recorded. Reference: GV-2024-0847. We will review within 48 hours."
Customizable Categories
Categories can be configured per deployment to match organizational structure and reporting requirements:
Categories are extracted automatically from the conversation content. The AI classifies based on keywords and context. New categories can be added by updating the system prompt - no code changes required.
Channel Comparison
🎙️ Real-time Voice (Hume)
- Live conversation
- Emotion detection
- Immediate clarification
- Best for complex cases
- Requires stable connection
💬 WhatsApp Voice
- Async recording
- Familiar platform
- Works offline (send later)
- Best for routine reports
- Low data usage
📞 USSD
- Menu-driven input
- Any phone (no smartphone)
- Zero data required
- Best for basic reports
- Limited detail capture
Cost Estimates (per message)
| Component | Service | Cost |
|---|---|---|
| WhatsApp Message (inbound) | Twilio | $0.005 |
| WhatsApp Message (outbound) | Twilio | $0.005 - $0.08* |
| Audio Transcription (2 min avg) | Whisper API | $0.012 |
| Translation (if needed) | GPT-3.5-turbo | ~$0.004 |
| Field Extraction | Claude Sonnet | ~$0.01 |
| Database Storage | Supabase | ~$0.001 |
| Total per WhatsApp Voice Submission | $0.04 - $0.12 | |
*Outbound cost varies by country and message type. Business-initiated messages cost more than user-initiated replies.
Implementation Timeline
With existing infrastructure in place, WhatsApp voice integration can be deployed in phases:
| Phase | Scope | Duration |
|---|---|---|
| Phase 1 | Twilio WhatsApp setup, webhook configuration, basic audio reception | 1-2 days |
| Phase 2 | Transcription pipeline, translation integration | 2-3 days |
| Phase 3 | Field extraction, database integration, confirmation flow | 2-3 days |
| Phase 4 | Testing, category customization, dashboard updates | 2-3 days |
Total estimated development time: 7-11 days
Prerequisites: Twilio account with WhatsApp Business API access, approved WhatsApp Business number