Overview
Weaviate is an open-source, AI-native vector database designed to help developers build and ship complete AI experiences. It unifies vector search, retrieval-augmented generation (RAG), and memory into a single, deployment-agnostic platform, giving teams the foundation they need to scale AI applications without worrying about data leakage or vendor lock-in.
Developers love Weaviate for its production-grade reliability and flexibility. With over 20 million open-source downloads and thousands of customers ranging from startups to large enterprises, it has proven itself as a core piece of the AI stack. Its efficient tenant system and built-in capabilities mean teams can handle billions of vectors and tens of thousands of segmented indexes with confidence.
Key Features
- Vector Database: Store, index, and search high-dimensional vectors at any scale, serving as the foundation for search, RAG, and AI agents.
- Query Agent: Ask questions in natural language; the agent automatically translates intent into optimized database queries.
- Built-in Embeddings: Generate vectors directly from text, images, and more without requiring an external embedding pipeline.
- Engram: Create personalized AI experiences that learn and adapt to each user over time, now generally available.
Use Cases
- RAG Applications: Build retrieval-augmented generation systems that deliver accurate, context-aware answers with reduced hallucination.
- Enterprise Search: Scale search across tens of thousands of tenants and billions of vectors for large-scale customer support and research workflows.
- Personalized AI: Deploy adaptive AI experiences that remember and learn from individual user interactions over time.
