Amsterdam-based Weaviate has raised $50 million in a Series B funding round to expand its team and further develop its open source database and cloud service to meet demands from the AI application development market.
"The Weaviate vector database is used as core infrastructure in the emerging AI-native ecosystem," says Weaviate CEO and co-founder, Bob van Luijt. "It allows users, from startups to enterprises, to create a new wave of applications ranging from custom-made search and recommendation systems to ChatGPT plugins."
The Weaviate AI-native vector database simplifies vector data management for AI developers solving the hard problem of generating, storing, and searching embedding vectors and their corresponding objects.
Its cloud service gives developers the full power of the Weaviate database without any of the operational overhead. And in February, the company introduced generative search support to make it easier for developers to harness the power of large language models (LLM) like GPT-4 and their human-like ability to seemingly understand and respond to queries in natural language.
"Weaviate's vector database and search engine provides a critical piece of infrastructure that's helping to drive a massive AI platform shift," says Index Ventures partner Erin Price-Wright. "The pace of adoption across enterprises and AI-native start-ups alike developing multimodal search, recommendation, and generative applications with Weaviate is incredible. This is the best-in-class product for developers building with AI and we are thrilled to be partnering with them to help drive the next phase of growth."
"With every major data-platform shift, we've seen the emergence of a new, underlying technology – and the explosion of generative AI is no different," says Dharmesh Thakker, a general partner at Battery Ventures. "Just as Elastic and MongoDB helped companies leverage non-tabular data, we believe Weaviate is poised to lead the revolution of vector databases, giving organisations critical tools to store, index and retrieve unstructured data through vector embeddings. We could not be more excited to partner with the Weaviate team and help the company refine its go-to-market program, particularly in the U.S."