Red Hat Introduces “Metal-to-Agent” AI Platform for the Hybrid Cloud

Red Hat announced Red Hat AI Enterprise — an integrated platform for deploying and managing AI models, agents, and applications across hybrid cloud environments. The solution is designed to deliver a complete “metal-to-agent” stack, spanning infrastructure and GPU-accelerated hardware through to AI models and agents that execute business logic.

The platform runs on Red Hat OpenShift — the company’s Kubernetes-based hybrid cloud environment — and provides scalable and secure management of AI workloads across any environment: on-premises, cloud, or edge.

Unified AI Infrastructure — From Hardware to Agents

Red Hat AI Enterprise provides:

• high-performance AI inference;
• model tuning and customization capabilities;
• deployment and management of AI agents;
• support for multiple AI models and hardware platforms;
• integrated observability and lifecycle management for AI solutions.
• According to Red Hat, the platform enables faster and more cost-effective AI deployment while supporting risk management and compliance through centralized control.

The company also introduced Red Hat AI 3.3 — an update to its AI portfolio that expands capabilities for managing and scaling AI across hybrid cloud environments. The combination of Linux, Kubernetes, and advanced inference and agentic capabilities aims to help organizations transition from isolated pilot projects to governed and autonomous AI operations. 

Red Hat AI Factory with Nvidia

In addition, Red Hat announced Red Hat AI Factory with Nvidia — a co-engineered software platform combining Red Hat AI Enterprise and Nvidia AI Enterprise.

The solution is designed to support the creation of “AI factories” — infrastructures that transform data into intelligence at scale. The platform helps IT teams manage both traditional infrastructure and AI technology stacks while providing a scalable foundation for AI deployments across data centers, cloud environments, and edge locations.

The focus is on security, high performance, and resilience across hybrid infrastructure environments.

Moving from AI Experimentation to Production Environments

According to Red Hat, for AI to deliver real business value, it must be integrated as a core component of the enterprise software stack rather than operating as a standalone initiative.

The company emphasizes that a stable hybrid cloud foundation enables organizations to build their own AI strategy and scale deployments with the same operational rigor applied to mission-critical IT systems.

Nvidia added that enterprises are increasingly building AI factories that require production-grade infrastructure and software capable of supporting agentic AI applications at scale.

Growing Enterprise AI Market

According to IDC forecasts, global enterprise AI spending is expected to exceed $1 trillion by 2029, with agentic AI applications serving as a primary growth driver.

Industrializing AI deployments is expected to be one of the key themes at the upcoming Mobile World Congress.