Embedding Feature Store

Embedding Feature Store is a ml service that serves consistent features to training and inference for vector representation of content or entities. It uses versioned feature definitions, freshness checks, and access policies so teams can avoid training-serving skew while keeping evidence, reliability, and public-safe operational boundaries clear.

“The machine learning team used Embedding Feature Store when the embedding index changed, so the team could avoid training-serving skew before the model moved into evaluation.”