Build a RAG Agent from Scratch | n8n Tutorial for Beginners (EP-4)

Описание: N8N Beginner To Pro Ai Agents Full Course
n8n Series EP-4 | Build Your Own RAG Agent (Step-by-Step Tutorial)

Welcome to Episode 4 of the n8n Automation Series!
In this video, you’ll learn how to build your own RAG (Retrieval-Augmented Generation) Agent step by step using n8n, even if you’re a beginner.
This tutorial shows how to combine AI + vector databases to create a smart, accurate, and context-aware AI agent.

By the end of this video, you’ll understand how a RAG agent retrieves information from stored knowledge and generates reliable answers — instead of guessing like normal AI.


🚀 What You’ll Learn in This Episode:
• What a RAG Agent is (simple explanation)
• How RAG works inside AI systems
• Vector database basics for beginners
• How data is stored as embeddings
• How to retrieve relevant context
• Connecting RAG with n8n workflows
• Step-by-step RAG agent build
• How to improve AI accuracy using RAG
• Real-world use cases of RAG agents
• Beginner-friendly end-to-end workflow


💡 Why Build a RAG Agent in n8n?
Normal AI guesses answers.
RAG Agents retrieve real information first, then generate responses — making them far more accurate and reliable.

With n8n, you can build powerful RAG agents without coding, perfect for knowledge bots, support systems, research assistants, and smart automation workflows.


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⚠️ Disclaimer:
This video is made for educational purposes only. All explanations are based on personal understanding and publicly available sources. This is NOT financial or legal advice. Tools and features may change over time. Always refer to official documentation for the latest updates.