In our journey through Retrieval-Augmented Generation, we've explored systems that work with unstructured text documents and structured data like SQL databases and CSV files. But these approaches have a fundamental limitation: they struggle to capture and leverage the rich web of relationships that exists within and across documents. Enter Graph RAG, a paradigm that transforms how we model, store, and retrieve information by explicitly representing knowledge as interconnected entities and relationships.