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This project demonstrates the creation of an intelligent Retrieval-Augmented Generation (RAG) chatbot using n8n, built to answer questions based on company documents stored in Google Drive. It automatically detects new or updated files, extracts and splits text into searchable chunks, and uses Google’s Gemini AI to generate embeddings and responses.
A vector database (such as Pinecone) indexes document content so the chatbot can efficiently retrieve the most relevant information for user queries. When a user asks a question, the system fetches related document segments, then uses the Gemini model to produce accurate, context-aware answers.
This workflow shows advanced automation integration, AI-driven indexing, and a fully automated conversational knowledge retrieval system for internal document support and knowledge access
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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