Bring AI-native applications to life with less hallucination, data leakage, and vendor lock-in
Hybrid Search
Improves search experiences by merging vector and keyword techniques for contextual, precise results.
Retrieval-Augmented Generation
Builds trustworthy generative AI applications using your own data and favorite LLMs.
Agentic AI
Fuels enterprise intelligence with scalable, context-aware AI agents that learn and adapt on the fly.
Flexible Cost-Performance Optimization
Drives efficient resource management tailored to the needs of your use case.
Weaviate is an open-source vector database designed to empower developers and enterprises to build and scale AI applications. It offers a developer-friendly environment that is cloud, model, and deployment agnostic, ensuring that it can integrate seamlessly with existing and future tech stacks. With over 1 million monthly downloads, Weaviate serves as a core piece of the AI-native stack, providing the necessary tools to create innovative applications while minimizing data leakage and vendor lock-in.
Weaviate supports lightning-fast pure vector similarity searches over raw vectors or data objects, even with filters. It allows users to bring their own vectors or utilize out-of-the-box modules for vectorization, ensuring compatibility with a wide variety of language model frameworks.
Building AI-native applications that require advanced search capabilities.
Creating generative AI applications that leverage proprietary data.
Developing scalable AI agents for enterprise intelligence.
Weaviate is an open-source vector database that helps developers build AI-native applications efficiently.
Yes, Weaviate can be deployed in various cloud environments, including serverless and enterprise cloud options.
Weaviate supports a wide range of integrations, allowing you to work with various language model frameworks and vectorization modules.
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