AI-Enabled eCommerce Search with Semantic Search and Weaviate

AI Impact Summary

E-commerce search is a critical driver of online sales, and poor search experiences lead to significant revenue loss. This project leverages semantic search with vector databases and Cohere’s multilingual embedding models to address common e-commerce search pitfalls like non-product searches and lack of multilingual support. By utilizing approximate nearest neighbor (ANN) algorithms, the system aims to deliver more relevant and accurate search results, ultimately improving the customer experience and potentially recovering lost sales.