RAG: Chat with Your Own Docs
Updated
For teams tired of answering the same policy questions. You'll start with the simplest version, an n8n agent that reads one Google Doc, then build real retrieval-augmented generation (RAG): load a handbook into a Pinecone vector database with n8n, and connect it to an n8n AI Agent that searches before every answer, cites its source and says "I don't know" instead of guessing.
Work through them in order: each step builds on the one before it, and every module runs in a practice copy of n8n right in your browser. It is free, and no experience is needed.
Advanced 3 modules about 40 minutes Free Start the path free
The path: 3 steps
- Step 1: A Support Agent That Answers from Your Own Docs✓ Done Advanced
Turn an n8n chat agent into a support agent that answers only from your policies in a Google Doc, refuses what it should, and hands off to a person by email.
Free · about 13 minutes · Watch the video · Read the guide · Next up: Make Your Handbook Searchable for an AI Helpdesk using Pinecone + n8n
- Step 2: Make Your Handbook Searchable for an AI Helpdesk using Pinecone + n8n✓ Done Advanced
Create a free Pinecone index, then build an n8n workflow that reads your handbook from Google Drive, cuts it into chunks, turns them into embeddings and stores them in Pinecone.
Free · about 14 minutes · Next up: Answer Staff Questions from Your Own Docs using n8n + Pinecone
- Step 3: Answer Staff Questions from Your Own Docs using n8n + Pinecone✓ Done Advanced
Build an n8n chat agent that searches your handbook in Pinecone before every answer, cites the page it came from, and says "I don't know" instead of guessing.
Free · about 13 minutes · Last step
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How every module works
Each step is shown on the left, with a cursor pointing to exactly where to click. You do the same thing on the right, in a practice copy of the real tool. Get it right and it moves on. Nothing touches your real accounts until you're ready to build it for real.
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