Weaviate is an open-source vector database designed for AI-native applications. It stores and indexes vector embeddings alongside their original data, enabling semantic search, recommendation systems, and retrieval-augmented generation (RAG). Weaviate supports hybrid search (combining vector and keyword search), automatic vectorization through integrated ML modules, and scales horizontally. A Moroccan startup building an AI-powered product search could use Weaviate to let customers find items by meaning rather than exact keywords.