Automated RAG System with n8n, Google Drive & Vector DB

A Retrieval-Augmented Generation (RAG) pipeline built in n8n that keeps a knowledge base up to date on its own. The workflow automatically detects any new or updated PDF in Google Drive, extracts the content, creates embeddings using OpenAI and stores everything in a vector database. Tested with a sample document, "ShopEase — Company Overview & Customer Information", the system returned accurate, document-based answers to every query, with no hallucinations. This setup suits businesses that need smart search, automated knowledge bases and chatbots that stay current in real time.

Built by Muhammad Ali, AI Automation Engineer & Full Stack Developer.