This workflow creates an AI-powered WhatsApp chatbot designed to assist customers in exploring Yamaha’s 2024 product brochure. It begins by importing and extracting content from a PDF brochure, then builds an in-memory vector store to enable natural language querying of the product information. When a customer sends a message via WhatsApp, the workflow filters for text messages and processes them through an AI agent trained to answer product-related questions. The AI uses the vector store to provide accurate, contextual responses, acting as a virtual sales assistant. Non-text messages are politely acknowledged with default responses, ensuring the chatbot handles diverse message types gracefully. This setup is ideal for businesses seeking an automated, interactive way to share product details and answer customer inquiries from WhatsApp, enhancing customer engagement and support.

Node Count

>20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreInMemory, extractFromFile, httpRequest, manualTrigger, stickyNote, switch, whatsApp, whatsAppTrigger