In this session, we’ll explore how Feast and Snowflake work together to build a powerful feature store that bridges batch and real-time AI workflows. You’ll learn how to efficiently store, process, and serve ML features with minimal data movement, optimizing both model performance and deployment speed.

Attendees will gain practical insights into streamlining end-to-end AI workflows, from data ingestion to model deployment. This session will equip you with the knowledge to optimize feature engineering pipelines and drive faster, more efficient AI model deployment.