Weaviate
Weaviate is an open-source, cloud-native vector database designed to simplify the development of AI-powered applications. It combines vector and hybrid search with a GraphQL API to enable semantic similarity, retrieval-augmented generation (RAG), and agentic AI workflows on structured and unstructured data. Built and maintained by SeMI Technologies, Weaviate provides fast, scalable indexing and querying of embedding vectors, powering use cases from semantic search to knowledge graphs.
Use Cases
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Semantic Search across documents, media, and internal knowledge bases
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Retrieval-Augmented Generation (RAG) for trustworthy, data-grounded chatbots
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Recommendation Systems leveraging vector similarity for personalization
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Knowledge Graphs linking entities and relationships in enterprise data
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Data Classification & Tagging using modular vectorizers for automated labeling
Customers & Markets
Weaviate serves developers and enterprises globally across technology, e-commerce, media, finance, and life sciences. Its open-source core and cloud offerings attract both startups and large organizations building AI-native products and RAG applications. The community exceeds 50,000 developers worldwide, and Weaviate is deployed in production for semantic search, virtual assistants, and real-time analytics.
Research, Partnerships & Innovations
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Research Focus: Scalable vector indexing (HNSW), hybrid search algorithms, agentic AI workflows, and open-source model integration
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Investors & Partnerships: Backed by Index Ventures, Battery Ventures, New Enterprise Associates, Zetta Venture Partners, and Cortical Ventures; integrates with OpenAI, Hugging Face, and cloud providers (AWS, Google Cloud, Azure)
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Innovations: First-mover in AI-native vector database, modular plugin architecture for custom vectorizers, GraphQL-first query interface, and seamless RAG support
Key People
Information on the executive leadership team is primarily maintained by SeMI Technologies and may be accessed via official channels.