From "Trust Me" to "Prove It": Why Enterprises Need Graph RAG

Ganesh | AI Engineer on Instagram: "If your RAG keeps pulling shallow or half-correct answers, the issue isn’t the LLM — it’s the retriever. Speaking from personal experience. Here’s how GraphRAG is one option to solve this problem👇 ⸻ 1️⃣ Plain RAG has a blind spot Vector search only finds similar text, not connected facts. So if the answer lives across multiple documents → RAG misses it. ⸻ 2️⃣ GraphRAG fixes this with a knowledge graph You can use llm to build graph for you once you describe t

GraphRAG: Ultimate RAG Engine - Semantic Search, Embeddings, Vector Search, & More!