Elastic and Red Hat: Scaling the sovereign AI factory with NVIDIA GPU acceleration

Power your sovereign AI factory using Elastic accelerated with the speed of NVIDIA GPUs on cuVS and the flexibility of Red Hat AI to enable enterprise-scale RAG and agentic AI workflows across any environment.

Rachael Wade

March 16, 2026

Summary

Elastic’s vector indexing with NVIDIA cuVS is now available with OpenShift on the Red Hat AI platform.
Elasticsearch and Red Hat AI integrated with NVIDIA provide organizations with a comprehensive platform compatible with native Kubernetes workloads.
Together, GPU-accelerated search and high-performance compute enables secure and scalable RAG deployments across hybrid cloud environments.

As generative AI solutions move beyond the pilot stage, enterprises are looking toward the AI factory for a standardized, repeatable infrastructure to run AI workloads at scale. A production-ready AI factory includes powerful models, real-time knowledge retrieval for context, agentic reasoning, and guardrails that keep proprietary data secure.

Organizations need these AI solutions to run wherever their business operates: on-premises, in the cloud, or across a hybrid footprint.

Together, Elastic and Red Hat are making that possible. Elastic’s GPU-accelerated vector search with NVIDIA cuVS is now available with OpenShift on the Red Hat AI platform. This collaboration equips enterprises with a production-ready foundation to deploy scalable search, retrieval augmented generation (RAG), and intelligent AI agents within their sovereign environments.

Why indexing speed matters from RAG to agentic AI

Successful enterprise AI deployments retrieve context from petabytes of unstructured proprietary company data. At the core of these RAG pipelines is vector search. However, as data volumes grow, building those vector indices often becomes a bottleneck that stalls deployments and drives high overhead costs.

By integrating with NVIDIA cuVS for GPU-accelerated indexing, Elastic offloads the compute intensive work during ingestion. The results are substantial:

Up to 12x faster indexing speeds
Up to 7x faster force merging
Lower CPU utilization

As a recommended vector database of the NVIDIA Enterprise AI Factory validated design, Elastic drives the engine for autonomous agents to reason and take action effectively with the most relevant data. Accelerated indexing means your agents are making decisions based on your real-time company data at scale.

Red Hat AI is the right platform for Elastic GPU-acceleration

Red Hat AI provides the Kubernetes-native foundation enterprises need to operationalize AI workloads from the data retrieval pipelines for model training to inference. Elastic with NVIDIA-acceleration combined with the Red Hat AI stack closes a critical gap for customers prioritizing sovereign AI.

By using Elastic Agent Builder and Elastic Workflows, developers can now build autonomous agents in their Red Hat AI on OpenShift AI. These agents will retrieve information and trigger operational workflows across your hybrid cloud, all while keeping your data and models within your environment.

“Red Hat OpenShift provides the essential, Kubernetes-native foundation for enterprises to operationalize and scale their AI workloads across any hybrid cloud environment,” said Katie Giglio, senior director, Ecosystem Development, Red Hat. “By enabling Elastic's GPU-accelerated search on Red Hat OpenShift and Red Hat AI with the speed of NVIDIA, we are jointly delivering a production-ready, open platform that empowers customers to build secure, high-performance RAG and autonomous AI agents while maintaining complete control over their data sovereignty.”

Deploy anywhere, keep your data in house

The collaboration between Elastic and Red Hat with NVIDIA gives organizations under strict data sovereignty regulations the flexibility to manage their data no matter where it lives.

Red Hat AI provides the foundation to host and secure models.
Elastic provides the context layer and agentic framework.
NVIDIA AI infrastructure delivers the performance acceleration.
Combined customers can seamlessly deploy agentic AI systems and operationalized AgentOps practices

Elastic with Red Hat AI ensures proprietary business data and models are deployed within the environment of your choice: your own data center, cloud regions, or hybrid architecture.

Elastic and Red Hat AI in action

Consider a financial institution facing the regulatory complexity and infrastructure costs of deploying a customer-facing AI assistant. To be effective, this AI assistant must run as an agent capable of checking customer account information and flagging suspicious activity in real time.

With Elastic GPU-accelerated search on the Red Hat AI platform, this financial organization can now:

Index new relevant data up to 12x faster as customer records are updated
Run autonomous agents that search across millions of vectors to retrieve relevant context and take action in real time
Deploy and scale its full AI pipeline within a single managed platform
Maintain complete control over data sovereignty and remain secure

Get started with Elastic on Red Hat AI

Elasticsearch with GPU acceleration is available on the Red Hat AI platform today. Whether you’re building that initial RAG application or deploying an AI factory at global scale, the combination of Elastic, Red Hat, and NVIDIA delivers the performance and flexibility required for modern AI solutions on an open source foundation.

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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