Weaviate is an open-source vector database designed to enable efficient storage and search of vector data. It facilitates semantic search by leveraging machine learning models to transform text into vector representations, allowing users to perform similarity searches beyond simple keyword matching. This is particularly useful for applications like natural language processing and recommendation systems, where context and meaning play crucial roles. Weaviate works closely with embeddings from models like BERT or GPT to enhance search relevance.