The integration of Generative AI (GenAI) with Knowledge Graphs is emerging as a powerful AI technique, enhancing knowledge management and Retrieval Augmented Generation (RAG). GenAI, while effective, is only one of many AI techniques. A notable example is Origin Trail's Decentralized Knowledge Graph (DRAG), which advances conventional graph retrieval-augmented generation by using decentralized knowledge management. This approach addresses the limitations of GenAI by incorporating graphs and hybrid retrieval methods, blending dense (deep learning-based) and sparse (term-matching) retrieval methods. This flexibility allows RAG to perform better on domain-specific tasks, such as legal text generation or medical Q&A, by retrieving data from diverse sources like Wikipedia, documentation, news, or custom datasets. According to Gartner, a stronger combination of AI techniques includes graphs and GenAI models.