Build a WhatsApp AI Chatbot with ChatGPT & APIs

Recommended architecture

The webhook-to-reply loop

1. Receive a customer message. BotLinkd sends the incoming message event to your webhook endpoint.
2. Validate and normalize the event. Confirm the signature or trusted source, extract sender, message text, media and conversation context.
3. Retrieve business knowledge. Search approved product docs, policy pages, FAQs or CRM data before asking the AI to answer.
4. Generate a safe response. Add system rules, escalation rules and business constraints so the AI does not invent unsupported answers.
5. Send the reply through BotLinkd. Use the BotLinkd API to send the message back to the customer on WhatsApp.

Important chatbot safeguards

• Human handover: route complaints, payment issues, legal-sensitive topics and uncertain answers to agents.
• AI pause controls: pause AI for one contact or platform-wide when a human needs to own the conversation.
• Source-grounded answers: use approved business data instead of allowing the AI to guess.
• Conversation memory: preserve useful context without exposing private or irrelevant customer data.
• Template awareness: use approved templates when the customer service window is not active.

Minimal webhook payload concept

{
  "event": "message.received",
  "from": "+911234567890",
  "message_type": "text",
  "text": "Where is my order #1048?",
  "contact_id": "customer_123",
  "timestamp": "2026-02-26T10:30:00Z"
}

Your server can use this event to look up the order, generate a short response and send the answer through the BotLinkd messaging API.

When no-code AI is better

A custom API chatbot is useful when your team needs complete control. Many businesses do not need that complexity. BotLinkd also supports AI-assisted workflows where teams can train an AI agent on business content and manage conversations from the dashboard.