Weaviate, developer of the AI-native Weaviate vector database, announced a $50M round of funding led by Index Ventures with participation from Battery Ventures. Weaviate’s existing investors include NEA, Cortical Ventures, Zetta Venture Partners, and ING Ventures. The capital will be used to expand the Weaviate team and accelerate the development of its open source database and new Weaviate Cloud Service for the AI application development markets use of embedding vectors, which are AI-generated representations of documents, images, customers, products, and other objects.
The Weaviate database simplifies vector data management for AI developers. An essential AI-native infrastructure component, it addresses the problem of generating, storing, and searching embedding vectors and their corresponding objects. AI-native vector database capabilities include:
- Extensible, built-in machine learning (ML) modules – Just load and search; Weaviate does the ML heavy lifting – any data type, any model, any use case.
- Rich vector search – Supports a variety of ML searches with the added benefit of being able to search vectors and the source objects from which the vectors were generated.
- High performance – Sub-second search, scales to billions of objects, runs non-stop.
