{"id":933761,"date":"2026-02-03T12:34:39","date_gmt":"2026-02-03T17:34:39","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/elastic-adds-high-precision-multilingual-reranking-to-elastic-inference-service-with-jina-models\/"},"modified":"2026-02-03T12:34:39","modified_gmt":"2026-02-03T17:34:39","slug":"elastic-adds-high-precision-multilingual-reranking-to-elastic-inference-service-with-jina-models","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/elastic-adds-high-precision-multilingual-reranking-to-elastic-inference-service-with-jina-models\/","title":{"rendered":"Elastic Adds High-Precision Multilingual Reranking to Elastic Inference Service with Jina Models"},"content":{"rendered":"

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Elastic Adds High-Precision Multilingual Reranking to Elastic Inference Service with Jina Models<\/b><\/p>\n

Two new Jina reranker models deliver low-latency, production-ready relevance for hybrid search and RAG workloads<\/i><\/p>\n

SAN FRANCISCO–(BUSINESS WIRE<\/a>)–
\nElastic (NYSE: ESTC), the Search AI Company, today made two Jina Rerankers available on Elastic Inference Service (EIS), a GPU-accelerated inference-as-a-service that makes it easy to run fast, high-quality inference without complex setup or hosting. These rerankers bring low-latency, high-precision multilingual reranking to the Elastic ecosystem.<\/p>\n

\nAs generative AI prototypes move into production-ready search and RAG systems, users run into relevance and inference latency limits, particularly for multilingual use cases. Rerankers improve search quality by reordering results based on semantic relevance, helping surface the most accurate matches for a query. They improve relevance across aggregated, multi-query results, without reindexing or pipeline changes. This makes them especially valuable for hybrid search, RAG, and context-engineering workflows where better context boosts downstream accuracy.<\/p>\n

\nBy delivering GPU-accelerated Jina rerankers as a managed service, Elastic enables teams to improve search and RAG accuracy without managing model infrastructure.<\/p>\n

\n\u201cSearch relevance is foundational to AI-driven experiences,\u201d said Steve Kearns, general manager, Search <\/b>at Elastic. \u201cBy bringing these Jina reranker models to Elastic Inference Service, we are enabling teams to deliver fast and accurate multilingual search, RAG, and agentic AI experiences, available out of the box with minimal setup.\u201d<\/p>\n

\nThe two new Jina reranker models are optimized for different production needs:<\/p>\n

Jina Reranker v2 (jina-reranker-v2-base-multilingual)
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<\/b>Built for scalable, agentic workflows.<\/p>\n