Generative AI has created new opportunities for enterprises to leverage data in powerful ways – from improving processes to creating entirely new products and services. But concerns loom large, namely the inaccuracy of LLM responses, otherwise known as “hallucinations.”
Join Juan Sequeda, Principal Scientist and Head of data.world's AI Lab 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.
Join this session to:
- Get a deep dive into the “Chat with Data Benchmark” and the 3X improvement a Knowledge Graph can have on LLM responses.
In addition, get an early look at how a data catalog built on a Knowledge Graph can enable clear explainability – ensuring that the LLM can “show its work” and find out how data governance can help ensure that LLMs don’t access sensitive data.
Speaker: Juan Sequeda
Principal Scientist, data.world

Juan F. Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. He holds a Ph.D. in Computer Science from The University of Texas at Austin. Wearing his scientific hat, Juan's goal is to reliably create knowledge from inscrutable data. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management, and what now is called Knowledge Graphs. Wearing his business hat, Juan is a product manager, does business development and strategy, technical sales, and works with customers to understand their problems to translate back to R&D.