Elastic Delivers GPU Infrastructure to Self-Managed Elasticsearch Customers via Cloud Connect

Elastic, the Search AI Company, announced the availability of Elastic Inference Service (EIS) via Cloud Connect for self-managed Elasticsearch deployments. Organizations can now gain on-demand access to cloud-hosted inference capabilities without managing GPU infrastructure, all while maintaining their core infrastructure and data on-premises. Users also gain immediate access to models by Jina.ai, an Elastic company and a leader in open-source multilingual and multimodal embeddings, rerankers, and small language models.

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Modern semantic search relies on vector embeddings for high-quality results. Now available in Elasticsearch 9.3, EIS on Cloud Connect allows self-managed customers to seamlessly leverage GPU-based embedding and reranking models, including leading Jina models, without the operational overhead of managing infrastructure. This enables teams to implement powerful semantic search capabilities quickly and efficiently. Self-managed clusters can keep their existing architecture and data in place while securely offloading embedding generation and search inference to Elastic Cloud’s managed GPU fleet.

“With Elastic Inference Service via Cloud Connect, we’re making it easier for self-managed customers to adopt semantic search without taking on the complexity of GPU infrastructure,” said Steve Kearns, general manager, Search at Elastic. “With a single setup, self-managed customers can access a range of cloud services from automated diagnostics to fast AI inference, all while keeping their data on-premises.”

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