WhatsApp and Call AI Automation
Budget: $14 – $30 NZD
AI Voice Bot + WhatsApp Automation System
1. Overview
Build a simple, stable AI automation system that handles:
Incoming phone calls with real-time AI voice conversation
WhatsApp automated chat flow
Customer data collection + price estimation + booking intent
System must be clean, minimal, and production-ready (no over-engineering).
2. Core System Architecture
Tech Stack:
Twilio (Voice + WhatsApp API)
OpenAI API (ChatGPT for AI conversation)
Backend (Node.js / Python – developer choice)
Flow:
Incoming Call → Twilio Voice → Speech-to-Text → OpenAI → Response → Text-to-Speech → Customer
↓
WhatsApp API (Twilio) → OpenAI → Automated Chat Flow
3. AI Voice Bot (Calls)
Requirements:
Answer incoming calls automatically
Natural human-like conversation (not IVR menu)
Real-time AI interaction (no pre-recorded flow)
Conversation Logic:
AI must:
Greet customer
Ask:
Type of cleaning (house / apartment / office)
Number of bedrooms
Number of bathrooms
Zip code
Extract structured data from user speech
Calculate price estimate based on predefined logic
Respond with estimated price range
Ask if customer wants to schedule
If yes → suggest continuing on WhatsApp
Technical:
Speech-to-Text (Twilio / Deepgram / Whisper)
AI processing via OpenAI (prompt-based structured output)
Text-to-Speech (Twilio TTS or similar natural voice)
4. WhatsApp Automation
Requirements:
Fully automated chat (no manual intervention)
Connected via Twilio WhatsApp API
Flow:
Auto-reply on incoming message
Ask same questions as voice bot:
Service type
Bedrooms / bathrooms
Zip code
Store responses
Calculate and return price estimate
Ask for booking confirmation
If confirmed → notify admin (simple message/log)
5. Pricing Logic System
Simple rule-based calculation (configurable):
Example:
Base price by service type
per bedroom
per bathroom
Optional zip-based adjustment
Must be easy to edit in code/config
6. AI System Behavior
Use OpenAI for:
Natural conversation
Understanding free speech input
Generating human-like responses
Must return structured output (JSON format) internally for:
service_type
bedrooms
bathrooms
zip_code
7. Admin Simplicity
No dashboard required
Keep system minimal
Logs can be simple (console / basic storage)
8. Setup & Configuration
Developer must:
Set up Twilio account (Voice + WhatsApp)
Configure phone number
Connect WhatsApp API
Integrate OpenAI API
Deploy backend (VPS or serverless)
Provide working endpoints
9. Testing & Delivery
Full testing of:
Call flow (real-time conversation)
WhatsApp automation
Pricing responses
Ensure system works end-to-end without errors
10. Final Deliverables
Fully working system
Source code
API keys configuration guide
Setup documentation (simple steps)
Basic usage instructions
11. Key Constraints
Must be simple and stable
No unnecessary features
No complex UI/dashboard
Focus on automation + reliability
12. Timeline
Total duration: 3–5 days
13. Success Criteria
AI handles calls naturally
AI understands user speech correctly
WhatsApp replies are fully automated
Price estimation works accurately
System runs independently without manual work
Timeline: 3 days
Budget: $30 NZD
1. Overview
Build a simple, stable AI automation system that handles:
Incoming phone calls with real-time AI voice conversation
WhatsApp automated chat flow
Customer data collection + price estimation + booking intent
System must be clean, minimal, and production-ready (no over-engineering).
2. Core System Architecture
Tech Stack:
Twilio (Voice + WhatsApp API)
OpenAI API (ChatGPT for AI conversation)
Backend (Node.js / Python – developer choice)
Flow:
Incoming Call → Twilio Voice → Speech-to-Text → OpenAI → Response → Text-to-Speech → Customer
↓
WhatsApp API (Twilio) → OpenAI → Automated Chat Flow
3. AI Voice Bot (Calls)
Requirements:
Answer incoming calls automatically
Natural human-like conversation (not IVR menu)
Real-time AI interaction (no pre-recorded flow)
Conversation Logic:
AI must:
Greet customer
Ask:
Type of cleaning (house / apartment / office)
Number of bedrooms
Number of bathrooms
Zip code
Extract structured data from user speech
Calculate price estimate based on predefined logic
Respond with estimated price range
Ask if customer wants to schedule
If yes → suggest continuing on WhatsApp
Technical:
Speech-to-Text (Twilio / Deepgram / Whisper)
AI processing via OpenAI (prompt-based structured output)
Text-to-Speech (Twilio TTS or similar natural voice)
4. WhatsApp Automation
Requirements:
Fully automated chat (no manual intervention)
Connected via Twilio WhatsApp API
Flow:
Auto-reply on incoming message
Ask same questions as voice bot:
Service type
Bedrooms / bathrooms
Zip code
Store responses
Calculate and return price estimate
Ask for booking confirmation
If confirmed → notify admin (simple message/log)
5. Pricing Logic System
Simple rule-based calculation (configurable):
Example:
Base price by service type
per bedroom
per bathroom
Optional zip-based adjustment
Must be easy to edit in code/config
6. AI System Behavior
Use OpenAI for:
Natural conversation
Understanding free speech input
Generating human-like responses
Must return structured output (JSON format) internally for:
service_type
bedrooms
bathrooms
zip_code
7. Admin Simplicity
No dashboard required
Keep system minimal
Logs can be simple (console / basic storage)
8. Setup & Configuration
Developer must:
Set up Twilio account (Voice + WhatsApp)
Configure phone number
Connect WhatsApp API
Integrate OpenAI API
Deploy backend (VPS or serverless)
Provide working endpoints
9. Testing & Delivery
Full testing of:
Call flow (real-time conversation)
WhatsApp automation
Pricing responses
Ensure system works end-to-end without errors
10. Final Deliverables
Fully working system
Source code
API keys configuration guide
Setup documentation (simple steps)
Basic usage instructions
11. Key Constraints
Must be simple and stable
No unnecessary features
No complex UI/dashboard
Focus on automation + reliability
12. Timeline
Total duration: 3–5 days
13. Success Criteria
AI handles calls naturally
AI understands user speech correctly
WhatsApp replies are fully automated
Price estimation works accurately
System runs independently without manual work
Timeline: 3 days
Budget: $30 NZD