Vector search
concept
Vector search compares fingerprints (embeddings) to find the closest matches. For shelf recognition it answers which known product a photo looks most like. Adding a new product is instant: store its fingerprint and search finds it.
For engineers: approximate nearest-neighbor (ANN) retrieval over an embedding index, with cosine distance and payload filters.