1d • General Discussion 💬
RAG Agents
ChatGPT and most AI tools answer using public internet data.
But what if you want answers only from your own business or personal data?
That’s where ✨ RAG Agents (Retrieval-Augmented Generation) step in.
Here’s how I built one with n8n:
- Trigger (Chat Message Received) → Listens for customer queries.
- AI Agent (Google Gemini) → Core brain of the agent.
- Vector Database (Pinecone) → Stores and retrieves your private data.
- Embeddings (Google Gemini) → Converts data into searchable vectors.
- Memory → Keeps chat context for natural conversations.
⚡ Outcome: Customer asks a question.
RAG Agent fetches the most relevant info from your data.
AI generates a precise, context-aware answer.
If no private data is needed → it works like a normal chatbot.
💡 In short:
RAG = Your Data + AI Power
5
4 comments
RAG Agents
skool.com/ai-automation-society
A community for mastering AI-driven automation and AI agents. Learn, collaborate, and optimize your workflows!
Leaderboard (30-day)
1
🔥
+3125
2
+873
3
+748
4
+524
5
🔥
+449
Powered by