Traditional RAG techniques have become obsolete in 2026. When you have a highly unstructured and scattered data across different repositories at your company, you can't expect contextually relevant and accurate responses with traditional RAG approaches. You first need to solve the data mess at your company. Convert the data into a structured format to use it in a RAG application. In the traditional RAG, we used such messy data and hence the results were all nonsensical. Then we started saying RAG is dead. But we should say - RAG isn't dead, the old RAG is dead. Now, how about processing the data well before using it for RAG? How about creating & understanding the relationship between the chunks in the data. I am talking about constructing a knowledge graph and feeding it to the RAG application? The results will be 100x better than the traditional RAG. In the image, you can see the indexing and querying sections of GraphRAG. Indexing is how your data gets indexed. You can see the knowledge graph construction. In the querying section, you can see the local as well as global search then retrieving the relationship between entities. Thereby building a more sophisticated RAG system that produces contextually relevant responses. I am impressed with this article by Renu Khandelwal on 'GraphRAG: Handling Complex Global Queries'. If you want to know more, you should read this article: ai.gopubby.com/graphrag-hand… Here is my guide on building GraphRAG with @LangChain & @SingleStoreDB in minutes: youtu.be/XI9Ph1-YYAE Also, this is my guide on enhancing RAG applications using Knowledge Graphs: youtu.be/rCQpQeJO59A

Learn to Build Agentic Applications in Minutes! Learn & level up your AI skills: youtu.be/I9OFXxY8rSw In this video, we’ll build a fully functional Agentic AI Application using LangGraph, @langchain , and @SingleStoreDB !

A Hands-On Guide to Model Context Protocol (MCP)! dev.to/pavanbelagatti/a-hand… @ThePracticalDev @SingleStoreDevs @SingleStoreDB

Learn how to build a fully functional Agentic AI Applications using LangGraph from @langchain & @SingleStoreDB! Here is my step-by-step guide: youtu.be/I9OFXxY8rSw