Feast is a feature store that bridges raw data and ML models by managing, storing, and serving features used in machine learning workflows. It allows teams to define, store, and retrieve features for both training and real-time serving, ensuring consistency between offline training and online inference. The system supports feature versioning, lineage tracking, and reuse across multiple models.