Join data.world’s Juan Sequeda, Principal Scientist & Head of our AI Lab, Dean Allemang, Principal Solutions Architect, and Bryon Jacob, CTO & Co-Founder, to see how a Knowledge Graph can improve the accuracy of LLM responses by 3X; and learn how a data catalog built on a Knowledge Graph can increase trust in LLMs with clear explainability and governance.
The data.world Data Catalog Platform creates a map of what data exists in your organization and ties it to meaning – context and semantics. With your data and knowledge in a flexible, Knowledge Graph format, AI-powered applications have the rich context needed to generate accurate, explainable, governed responses.
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By sharing enterprise meaning – context and semantics, a data catalog built on a Knowledge Graph boosts the relevancy and correctness of LLM responses.
Where LLMs were a black box, now they can literally show their work. With data.world, it’s possible to directly trace LLM responses to enterprise knowledge.
With proper governance in place with data.world, your organization can limit what LLMs can access — keeping confidential and proprietary information from being exposed.
“If you don’t choose a data catalog platform on a knowledge-graph architecture, and bring in all data and knowledge, governed in one platform, then you are setting yourself up for failure in an AI future.”
A data catalog built on a Knowledge Graph complements the power of Large Language Models, combining trust and accountability with powerful language proficiency to enable scalable AI applications.
New benchmark examines LLM accuracy for Question Answering on Enterprise SQL Databases and the improvements offered by a Knowledge Graph
A knowledge graph is the optimal foundation for enterprise AI and the only way to truly activate metadata. data.world is the only data catalog built on a knowledge graph architecture with a framework for embeddable AI bots that increases the automation for cataloging, data governance, and DataOps.
