Executive Summary

Integrating AI models into the WhatsApp Business Cloud API allows businesses to replace manual customer service representatives with 24/7 intelligent sales agents that qualify leads, answer inventory queries, and sync lead data to CRM databases.

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1. Architecture Overview

A production WhatsApp AI integration consists of 3 architectural layers:

code
[ WhatsApp Business API ] ──(Webhook)──> [ Next.js Route Handler ] ──> [ Google Gemini 1.5 Flash ]

│


└──> [ CRM Database ]

1. Meta Webhook Listener: Receives incoming user messages via POST requests.

2. AI Agent Processing Engine: Sends message context + function definitions to Google Gemini 1.5 Flash or Claude 3.5 Sonnet.

3. Outbound Cloud API Dispatch: Calls Meta's /v20.0/PHONE_NUMBER_ID/messages endpoint to send instant responses back to the user.

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2. Key Code Implementation

typescript
// app/api/whatsapp/webhook/route.ts

import { NextResponse } from 'next/server';


import { GoogleGenerativeAI } from '@google/generative-ai';



const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);



export async function POST(req: Request) {


const body = await req.json();


const message = body.entry?.[0]?.changes?.[0]?.value?.messages?.[0];



if (message && message.text) {


const userText = message.text.body;


const model = genAI.getGenerativeModel({ model: 'gemini-1.5-flash' });


const result = await model.generateContent(userText);


const aiReply = result.response.text();



await sendWhatsAppMessage(message.from, aiReply);


}



return NextResponse.json({ status: 'ok' });


}

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