Create AI Chatbots with Supabase Search in n8n Workflows

Transform your documents into an intelligent AI chatbot that can answer questions based on your content using this comprehensive n8n workflow that combines Supabase vector storage with advanced RAG (Retrieval-Augmented Generation) technology.

What this workflow does

This powerful automation creates a complete document chat assistant system within n8n. The workflow automatically downloads documents from Google Drive, extracts text from PDFs, and converts them into AI embeddings that are stored in Supabase's pgvector database. When users ask questions through the webhook endpoint, the system performs semantic search to find the most relevant document chunks and generates accurate, grounded responses using AI models from OpenRouter, Gemini, or OpenAI.

The process includes recursive text chunking for optimal content processing, intelligent embeddings generation, and seamless integration with your frontend applications through webhook API endpoints.

Use cases

• Customer support automation: Create chatbots that answer questions based on your knowledge base, manuals, and FAQ documents
• Internal knowledge management: Build AI assistants for employee onboarding, policy questions, and company documentation
• Educational platforms: Develop smart tutoring systems that can answer questions about course materials and textbooks
• Legal and compliance: Create AI helpers that can reference contracts, regulations, and legal documents
• Product documentation: Build intelligent help systems that provide instant answers from technical documentation

Technical details

This n8n workflow leverages multiple specialized nodes including webhook triggers, Google Drive integration, LangChain agent nodes for AI processing, and ChatOpenRouter for model connectivity. The system utilizes Supabase's pgvector extension for efficient vector storage and semantic search capabilities.

The two-pipeline architecture ensures smooth operation: the document ingestion pipeline handles content processing and storage, while the RAG chat pipeline manages real-time question answering with contextually relevant responses.

Ready to deploy with your n8n instance, Supabase account, Google Drive, and preferred AI provider credentials.