Semantic product search that finds it when a shopper describes it

+24%search-to-cart conversion

Embeddings across 40,000 products, so “something for a shady balcony” returns plants that grow in the shade.

The problem

Shoppers searched the way they talk, and keyword search returned nothing for anything but exact product names.

Embeddings across 40,000 products and their descriptions, combined with keyword search for brands and sizes, served from a vector database.

Search-to-cart conversion rose by 24%, most of it from searches that used to return no results.

Thirty minutes with the founder about one process in your operation. Nothing to prepare.