This n8n workflow automates a WhatsApp-based AI chatbot designed to assist customers in navigating a product catalog, specifically Yamaha powered loudspeakers for 2024. The workflow begins by importing a PDF brochure via an HTTP request and extracting its text content to build an in-memory vector store. This knowledge base enables the AI to answer customer queries naturally. When a customer sends a message via WhatsApp, the workflow filters for text messages, then processes the input through an AI language model configured as a sales agent. The AI accesses the product catalog stored as embeddings and provides relevant responses or directs users to further information. The entire setup creates an interactive, self-service customer support tool ideal for sales and product inquiries, enhancing engagement and information delivery through WhatsApp.
WhatsApp AI Chatbot for Product Catalog Query
| 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 |
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