Felix Liao
As AI applications grow more sophisticated, the divide between structured and unstructured data has become one of the most significant bottlenecks in enterprise architecture. Building reliable, AI-ready pipelines means managing relational data, documents, images, and embeddings — often across disconnected systems, with no unified layer to govern or deliver them cohesively.
Join Felix Liao, Director of Product Management at Denodo, for a deep dive into Denodo's newly introduced Vector column type and functions in the 9.4 release — a milestone capability that brings structured and unstructured data together under a single, governed data delivery layer. Whether you're architecting RAG pipelines, building semantic search, or enabling AI applications that span both data types, Denodo 9.4 gives you the foundation to do it with confidence and control.
In this session, you'll learn:
- How Denodo's new Vector support simplifies the development of AI applications that combine structured and unstructured data sources
- How to design and govern unified data products that support embedding-based workloads alongside traditional relational queries
- Real-world patterns for integrating Denodo's vector capabilities into modern AI architectures, including RAG pipelines and semantic search
