When Similarity Isn’t Accuracy in GenAI: Vector RAG vs GraphRAG

Retrieval-augmented generation (RAG) based applications are being developed in high numbers with the advent of large language models (LLM) models. We are observing numerous use cases evolving around RAG and similar mechanisms, where we provide the enterprise context to LLMs to answer enterprise-specific questions. Today, most enterprises have developed, or are in the process of developing, a knowledge base based on the plethora of documents and content they have accumulated over the years. Billions of documents are going through parsing, chunking, and tokenization, and finally, vector embeddings are getting generated and stored in vector stores.