May 29, 2023

News Stories from the Digital World

Weaviate raises $50 million to meet ‘soaring demand for AI native vector database technology’, developer of the AI-native Weaviate vector database, has completed a $50 million round of funding led by Index Ventures with participation from Battery Ventures.

Weaviate’s existing investors, including NEA, Cortical Ventures, Zetta Venture Partners, and ING Ventures also joined this round.

The capital will be used to expand the Weaviate team and accelerate the development of its popular open source database and new Weaviate Cloud Service to satisfy the rapidly growing AI application development market.

Global spending on artificial intelligence technology and services is expected to reach $154 billion in 2023 and surpass $300 billion in 2026, according to technology research company IDC.

This massive wave of application development will be powered by a new type of data, embedding vectors, which are AI-generated representations of documents, images, customers, products, and other objects.

A company called Weaviate says its AI-native vector database is “essential to the growth of AI applications, including generative AI”.

It is used by developers who need to generate, store, share, and search millions or even billions of vectors, very often in real-time.

Bob van Luijt, Weaviate CEO and co-founder, says: “The Weaviate vector database is used as core infrastructure in the emerging AI-native ecosystem.

“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.”

Simpler AI development

The Weaviate database simplifies vector data management for AI developers.

An essential AI-native infrastructure component, it solves the hard 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.
  • Richer 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.

Since raising its series A funding in early 2022, Weaviate has seen open source downloads pass the 2 million mark.

Weaviate has also launched a new Weaviate Cloud Service, which gives developers the full power of the Weaviate database without any of the operational overhead.

The Weaviate Cloud Service is available immediately and can be used for free for 14 days.

Erin Price-Wright, Index Ventures partner, says: “Weaviate’s vector database and search engine provides a critical piece of infrastructure that’s helping to drive a massive AI platform shift.

“The pace of adoption across enterprises and AI-native startups 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.”

In February, the company introduced generative search support to make it easier for developers to meaningfully 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.

Dharmesh Thakker, a general partner at Battery Ventures, says: “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.

“Just as Elastic and MongoDB helped companies leverage non-tabular data, we believe Weaviate is poised to lead the revolution of vector databases, giving organizations 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 US.”