Templates / Handle WhatsApp sales queries with GPT-4, Supabase, and a product catalog

Handle WhatsApp sales queries with GPT-4, Supabase, and a product catalog

Needs changes

by Shadrack ✓ · 2,455 views · created 2026-02-04 · Lead Nurturing, AI Chatbot

Needs changes. This template uses 2 thing(s) that n8n 3.0 removes: SerpApi (Google Search), AI Agent v1 (old agent modes). 2 breaking item(s) found. Static check, last run 2026-10-19.

What to replace before upgrading

Removed in 3.0Replace with
SerpApi (Google Search)
Web Search
No direct replacement: call the SerpApi REST API with an HTTP Request tool, or use a verified community node
AI Agent v1 (old agent modes)
Sales AI agent (v1.9)
Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Nodes used (18)

Embeddings OpenAISupabase Vector StoreRecursive Character Text SplitterDefault Data LoaderWhatsApp Business CloudOpenAISerpApi (Google Search)Data tableOpenAI Chat ModelSimple MemoryAI Agent

What it does

How it works An AI-powered sales agent on WhatsApp that handles product inquiries using your Supabase knowledge base and n8n catalog. Customers can send text, voice notes, or images to ask about products, pricing, and specs. The agent responds with detailed answers, product images, and FAQs, creating a complete self-service sales experience. (I primarily designed this for furniture business, consider tailoring it) Setup steps Connect Supabase credentials for your knowledge base and FAQs Configure n8n tables with your product catalog (prices, descriptions, image links) Set up WhatsApp Business API integration Add your product categories and common queries to the AI context Test with sample product questions and image uploads Customization tips Structure your catalog tables with clear columns (SKU, price, description, imageurl) Add industry-specific terminology to the AI prompt Create templated responses for common FAQs to ensure consistency Enable voice-to-text transcription for better voice note handling Add product recommendation logic based on customer queries Set up image recognition for customers sending product photos to identify items

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