How to Build a RAG Agent in n8n
Build a RAG Agent in n8n with Jessica Singh
You've built a few automations. But what if your workflow could actually pull from your own data and respond intelligently?
Join us for a hands-on workshop with Jessica Singh as she walks you through building a RAG (Retrieval-Augmented Generation) agent in n8n — an AI agent that retrieves information from your documents and data to generate smart, context-aware responses instead of generic chatbot answers.
This session assumes some automation background, so we're skipping the basics and jumping straight into the build. Jessica will walk through the full architecture of a RAG agent — vector stores, embeddings, data loaders — then build one live so you can follow along. She'll also share her GitHub repo so you can export the workflow and customize it on your own.
About AI Snack Club 🧃
AI Snack Club is a community where ambitious women learn AI together — through expert-led workshops, a private Slack, a template library, and peer learning. We translate what's happening in the SF tech bubble into actionable lessons, test prompts, and share what actually works.