Red Hat has announced Red Hat AI Enterprise, a new integrated AI platform designed to help organisations deploy and manage AI models, agents and applications across hybrid cloud environments.
The launch expands the company’s AI portfolio, which already includes Red Hat AI Inference Server, Red Hat OpenShift AI and Red Hat Enterprise Linux AI, and is accompanied by the release of Red Hat AI 3.3, featuring major updates across its AI stack.
The company says the platform provides a comprehensive “metal-to-agent” stack,” integrating Linux and Kubernetes infrastructure with AI inference and agentic capabilities. The goal is to help enterprises move beyond fragmented AI experimentation and into governed, production-grade deployments.
Many organisations remain stuck in the AI pilot phase due to fragmented tooling and inconsistent infrastructure, according to Red Hat
Red Hat AI Enterprise aims to unify model and application lifecycles. It hopes to enable IT teams to manage AI as a standardised enterprise system rather than siloed projects.
Built on Red Hat OpenShift, the platform supports deployment across multiple environments, hardware architectures and cloud infrastructures.
Key Features of Red Hat AI Enterprise
Red Hat highlighted several core capabilities
- Optimised AI inference using the vLLM inference engine and llm-d distributed inference framework
- Integrated observability and lifecycle governance for enterprise AI workloads
- Hybrid cloud flexibility to deploy models and agents across environments
- Support for a wide range of models and hardware platforms
Joe Fernandes, Vice President and General Manager of the AI Business Unit at Red Hat, said the platform is designed to make AI a core component of enterprise software stacks rather than a standalone experiment.
“With Red Hat AI Enterprise and Red Hat AI 3.3, organisations can move beyond fragmented pilots to governed, repeatable and high-performance AI operations across the hybrid cloud,” he said.
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