Elastic and Jina AI join forces to advance open source retrieval for AI applications

Retrieval lies at the core of the Elastic Search AI Platform. Over the years, we’ve worked hard to provide powerful search relevance to help users find and analyze exactly what they need in real time. To add to the momentum, we are thrilled to announce today that Elastic has joined forces with Jina AI, a pioneer in open source multimodal and multilingual embeddings, reranker, and small language models.

Great AI experiences come from combining LLMs with the right context and proprietary data. Jina AI brings deep expertise in search foundation models to help businesses build the best retrieval solutions. We’re excited about the capabilities that they bring, including:

• Universal embeddings models for text and image understanding with support for single-vector and multi-vector embeddings outputs

• Advanced rerankers for retrieving visual documents with state-of-the-art performance on long multilingual documents and code searching tasks

• Small language models for HTML-to-Markdown conversion and HTML-to-JSON extraction with exceptional quality

We will continue to offer Jina AI’s models on Hugging Face for users to download them for free. We will also make their models available via the Elastic Inference Service (EIS) on Elastic Cloud, so customers can run embeddings and rerankers natively alongside Elastic vector search. 

We asked Han Xiao, former CEO of Jina AI and newly appointed VP of AI at Elastic, to share some words on the company and what it means to join Elastic:

I’m delighted to welcome the Jina AI team as we continue building the world’s best platform for search and AI, and we look forward to sharing what we will achieve together.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

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