A semantic layer is a business translation layer that sits between your data and your data consumers (like human users or AI agents).
A semantic layer is critical for AI agents because it condenses and standardizes business logic so that generic LLMs can better understand your business. Traditionally, semantic layer was embedded within a BI tool and was created manually. But as AI agents become the primary way of retrieving information, the process of building semantic layers needs to be scalable and semantic layers need to be decoupled from downstream tools.
In this talk, we explore a few common approaches to building AI friendly semantic layers.
Jinlin He is a Data scientist turned Solutions Architect at Databricks with 6+ years in ML/AI engineering and pre-sales. She enjoys the intersection of systematic problem solving and open-ended search space in technical sales.
Rob Bajra is a Solutions Architect with Databricks based in New York City. Rob specializes at the intersection of agents and data apps. With a background in AI engineering and data science, Rob has led the development of influencer marketplaces, digital twins and dynamic pricing systems. Rob has previously worked as an AI Engineer at JetBlue Airways and Data Scientist at Southwest Airlines.
