-

Elasticsearch Open Inference API now Supports Jina AI Embeddings and Rerank Model

Developers using Elastic to build search and RAG applications can now use the latest Jina AI embedding and reranking models without additional integration or development costs

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced the Elasticsearch Open Inference API now supports Jina AI’s latest embedding models and reranking products. Developers building semantic search and RAG applications with the Elasticsearch vector database now benefit from Jina AI’s high-performance, cost-effective tools for GenAI information retrieval and semantic applications. This integration includes support for multilingual text embeddings and multilingual reranking, and is optimized for retrieval, clustering, and classification.

“Integrating Jina AI’s embeddings and reranker models with the Elasticsearch Open Inference API brings enterprise-grade semantic search to production environments while strengthening our open-source communities,” said Dr. Saahil Ognawala, head of product at Jina AI. “Combining Jina’s resource-efficient and open-weight search foundation models with Elasticsearch's proven scalability enables developers to easily build reliable semantic search and RAG applications.”

“Elastic is committed to providing open GenAI solutions that enable developers to build the next generation of search experiences,” said Ajay Nair, general manager, Platform at Elastic. “Our collaboration with Jina AI gives our users access to Jina’s high-performance tools on a singular Elasticsearch platform alongside Elastic models like ELSER, providing a seamless, streamlined building experience designed to create first-class generative AI applications.”

Support for Jina AI is available today in Elastic Cloud Serverless. Supported Jina AI models include jina-embeddings-v3, jina-reranker-v2-base-multilingual, and more. For a full list of supported models, read the Elastic blog.

About Elastic

Elastic (NYSE: ESTC), the Search AI Company, enables everyone to find the answers they need in real-time using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform, the development platform used by thousands of companies, including more than 50% of the Fortune 500. Learn more at elastic.co.

Elastic and associated marks are trademarks or registered trademarks of Elastic N.V. and its subsidiaries. All other company and product names may be trademarks of their respective owners.

Contacts

Media Contact
Elastic PR
PR-team@elastic.co

Elastic N.V.

NYSE:ESTC

Release Versions

Contacts

Media Contact
Elastic PR
PR-team@elastic.co

More News From Elastic N.V.

Elastic Named a Leader in the IDC MarketScape: Worldwide SIEM 2026

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, today announced that it has been named a Leader in the IDC MarketScape: Worldwide SIEM 2026 Vendor Assessment (Doc# US54126826, June 2026). Download the complimentary excerpt here. The IDC MarketScape’s assessment highlights several key strengths of Elastic Security, including: Elastic Common Schema and the underlying Elasticsearch engine allow customers to query security and operational data using a single language. C...

Elastic Named a Strong Performer in Extended Detection And Response Platforms, Q2 2026

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, today announced that it has been named a Strong Performer in The Forrester Wave™: Extended Detection And Response Platforms, Q2 2026. The report recognized Elastic Security’s SIEM-replacement capabilities, open data architecture, AI innovation, and endpoint protection. Access the complimentary report here. Elastic Security is an agentic security operations platform that unifies SIEM, XDR, and native automation. Elastic...

Elastic Observability Gives SREs a Head Start on Kubernetes Incident Investigations

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, today introduced an agentic Kubernetes investigation workflow and MCP-based observability skills that diagnose incidents the moment an alert fires. By the time an SRE opens the alert, the root cause has already been identified, evidence has been assembled, and recommended next steps have been surfaced. For teams running Kubernetes at scale, the gap between alert and answer costs time, compounds outages, and wears down...
Back to Newsroom