How would you design a KNN-based recommendation system?

You represent users/items as embeddings and use nearest neighbor search to retrieve similar items or users.

A production KNN recommender converts users or items into vector embeddings, stores them in an ANN index, and retrieves nearest neighbors for recommendations. Additional layers like filtering, ranking, and business rules are applied.