Next Generation AI Vector Database
What is Weaviate?
Weaviate is a production-ready, open-source vector database designed to power AI-native applications at scale. It handles embeddings, ranking, and auto-scaling, and supports features like Retrieval Augmented Generation (RAG), Hybrid Search, and Agentic AI. It’s language-agnostic and can be used with SDKs for Python, Go, TypeScript, and JavaScript, or via GraphQL/REST APIs. You can run Weaviate in the cloud or on your own infrastructure.
What is Weaviate's Hybrid Search and how does it improve search experiences?
Weaviate's Hybrid Search blends vector search with traditional keyword search to deliver more contextual and precise results across all your data. By combining semantic understanding with keyword signals, you get more accurate and relevant results with less effort.
What is Retrieval Augmented Generation (RAG) in Weaviate?
Retrieval Augmented Generation enables trustworthy chat experiences grounded in your data, integrating retrieval with generation to produce responses that reflect your information.
What is Agentic AI in Weaviate?
Agentic AI refers to Knowledgeable AI agents and agentic workflows that Weaviate provides to help automate data interactions and AI-powered processes.
How does Weaviate facilitate the development of AI-native applications?
Weaviate provides a flexible, open-source vector database foundation with extensive developer resources (docs, tutorials, community). It supports integration with language models, retrieval-augmented generation, and cost-performance optimization to help you prototype and scale AI apps while minimizing data leakage risk and vendor lock-in.
What integrations does Weaviate support for building AI applications?
You can bring your own vectors or use Weaviate's out-of-the-box vectorization modules. Weaviate connects with popular LM frameworks (e.g., LangChain, LlamaIndex) and works with major LLMs from providers like OpenAI.
How can I deploy Weaviate?
Weaviate can be deployed in the cloud (Weaviate Cloud) or on your own cloud. It supports enterprise-ready deployment with security features such as RBAC, SOC 2, and HIPAA compliance.
What languages and SDKs does Weaviate support?
Weaviate is language-agnostic by design. It provides SDKs for Python, Go, TypeScript, and JavaScript, and also supports GraphQL and REST APIs.
Does Weaviate provide built-in embeddings?
Yes. Weaviate can handle embeddings directly (built-in embedding service) or connect to your own ML models.
How do I get started with Weaviate?
You can try Weaviate Cloud today, or follow the Quickstart and docs to spin up a cluster, point it at your data, and begin using embeddings, ranking, and AI features.
Is Weaviate open-source?
Yes. Weaviate is an open-source vector database with a strong community and broad adoption.
What security and compliance capabilities does Weaviate offer?
Weaviate supports enterprise-grade deployment including RBAC, SOC 2, and HIPAA to help meet security and compliance requirements.
What learning resources are available for Weaviate?
Weaviate offers a Learning Center, events, blog, and comprehensive documentation to help you build and optimize AI-powered solutions.
