RAG vs Agentic RAG vs Graph RAG Explained | Which AI Retrieval Architecture Wins? | Bazai

What's the difference between RAG, Agentic RAG, and Graph RAG? In this video, Bazai explains the three most important Retrieval-Augmented Generation architectures powering modern AI applications. You'll learn: ✅ What Traditional RAG is and how it works ✅ How Agentic RAG uses AI planning, reasoning, and tools ✅ Why Graph RAG understands relationships instead of just documents ✅ When to use each architecture in real-world AI systems ✅ Which approach is best for enterprise AI, chatbots, copilots, and AI agents Whether you're building with OpenAI, Claude, Gemini, Llama, LangChain, LangGraph, CrewAI, AutoGen, MCP, or vector databases like Pinecone, Weaviate, ChromaDB, and Milvus, this video will help you understand which retrieval architecture fits your use case. Chapters 00:00 Introduction 00:18 What is RAG? 00:52 What is Agentic RAG? 01:28 What is Graph RAG? 02:10 Which One Should You Choose? 02:35 Final Thoughts 🔥 Subscribe to Bazai for videos on: AI Agents Agentic AI RAG Systems Graph RAG MCP Servers LangGraph Enterprise AI LLM Engineering Generative AI Multi-Agent Systems AI Automation Cloud AI 📌 New AI videos every week. #AI #RAG #AgenticAI #GraphRAG #LLM #OpenAI #LangChain #LangGraph #GenerativeAI #Bazai