Building Agentic Knowledge Graphs for RAG

Hack Session

About the session

As organizations scale their Generative AI initiatives, traditional Retrieval-Augmented Generation (RAG) architectures are increasingly challenged by fragmented data, missing context, and limited reasoning capabilities. Knowledge graphs offer a powerful solution by capturing the rich relationships that exist across structured and unstructured enterprise data, enabling more accurate, explainable, and context-aware AI systems.As organizations scale their Generative AI initiatives, traditional Retrieval-Augmented Generation (RAG) architectures are increasingly challenged by fragmented data, missing context, and limited reasoning capabilities. Knowledge graphs offer a powerful solution by capturing the rich relationships that exist across structured and unstructured enterprise data, enabling more accurate, explainable, and context-aware AI systems.

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