This n8n workflow implements an Agentic Retrieval Augmented Generation (RAG) system that processes diverse data types using a Superbase vector database and SQL queries for tabular data. The system dynamically retrieves, embeds, and aggregates PDF content and structured sales data while using file content fetching and error-handling nodes. Built by Nate Herk with a featured template by Cole, it offers a robust, free automation template to enhance AI agent reasoning before querying.

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