In the era of big data, large language models (LLMs) are becoming increasingly important for tasks like question answering, document analysis, and chatbot development. However, traditional LLMs often need help with factual accuracy, reasoning, and complex information handling.

This talk introduces GraphRAG, a novel technique that leverages the power of knowledge graphs to empower LLMs. We’ll delve into the limitations of traditional LLMs and vector-only approaches of RAG and explore how GraphRAG bridges the gap. GraphRAG equips LLMs with a deeper understanding of the world by utilizing enterprise data, boosting their accuracy and reasoning abilities, and handling complex information.

This talk will explore the exciting world of GraphRAG and showcase its potential to revolutionize various fields. We will also discuss real-world applications and case studies to illustrate the benefits of GraphRAG for practitioners compared to a vector-only approach.