In depth
Traditional recommendation engines use purchase history and collaborative filtering to suggest "people also bought" rows. An AI chatbot operates in a tighter loop: the shopper states a need in the current conversation, and the chat returns one product with reasoning tied to that need. Emporiqa retrieves candidates from your catalog by meaning (vector search) and reranks them, then the chat presents the best match with price, stock, and an add-to-cart button. Recommendations are grounded in your own catalog, so everything the shopper sees is in stock and linked to your checkout.
See also