-
Products & documentation Red Hat AI
A platform of products and services for the development and deployment of AI across the hybrid cloud.
Red Hat AI Enterprise
Build, develop, and deploy AI-powered applications across the hybrid cloud.
Red Hat AI Inference
Optimize model performance with an integrated stack for fast, consistent, and cost-effective inference at scale.
Red Hat Enterprise Linux AI
Develop, test, and run generative AI models to power enterprise applications.
Red Hat OpenShift AI
Build and deploy AI-enabled applications and models at scale across hybrid environments.
-
Learn Basics
-
AI partners
Red Hat OpenShift AI
Red Hat® OpenShift® AI is a flexible hybrid cloud platform to deploy open weight models and autonomous agents at scale.
Quick links
This video can't play due to privacy settings
To change your settings, select the "Cookie Preferences" link in the footer and opt in to "Advertising Cookies."
Watch a Red Hat OpenShift AI demo. Video duration: 5:59
What is Red Hat OpenShift AI?
Red Hat OpenShift AI combines comprehensive MLOps, GenAIOps, and AgentOps capabilities to accelerate the deployment of agentic AI applications into production.
With open source tools like PyTorch, Kubeflow, MLflow, and vLLM, teams can experiment, serve, and deliver AI models and applications at scale.
Benefits
Efficiency
Access pre-built or customized cluster images and use your preferred frameworks. Use AI tooling that has been tested and validated by Red Hat, so you can focus on what’s important.
Control
Manage costs, data privacy, and agent lifecycles reliably for a stable MLOps foundation. Improve visibility with our optimized, production-ready, third-party models validated for Red Hat OpenShift AI.
Flexibility
Collaborate with data scientists, AI engineers, and developers in a single AI application platform and deploy your models across the hybrid cloud: on premise, at the edge, or in disconnected environments.
AI safety and security
When you’re scaling quickly, you don’t want security threats to slow you down. With Red Hat OpenShift AI, you get extra visibility while you scale.
Filter toxic, biased, or off-topic inputs and outputs to maintain fairness and safety. Protect models from bad actors with tools like real-time NeMo guardrails and use adversarial vulnerability scanning to prevent hallucination and bias.
This video can't play due to privacy settings
To change your settings, select the "Cookie Preferences" link in the footer and opt in to "Advertising Cookies."
Learn how to protect your gen AI models. Video duration:10:02
Product highlights
| Feature | Details | Benefit |
|---|---|---|
Agentic AI | Implement AgentOps for agentic AI, using MLflow. | Get end-to-end traceability of your models and tools. |
vLLM | vLLM helps manage costs of gen AI inference by using GPU resources efficiently. | Speed up AI inference with lower cost-per-token and stable latency at scale. |
MCP servers | Model context protocol (MCP) servers actively govern and translate external tool access. | This streamlines your agentic workflows with managed access and security. |
Private AI | Private AI provides on-premise and disconnected mode support. | Strengthen your digital sovereignty strategy with a layer for AI. |
Models-as-a-Service | MaaS shifts IT from token consumers to internal providers. | Gain developer-governed, self-service access to high-performing models. |
llm-d | llm-d provides well-lit paths in an open source framework to optimize complex LLMs at scale. | Get more out of your AI infrastructure running on your Kubernetes distributions of choice. |
AI hub | AI hub provides performance insights from third-party model validation. | Centrally manage trusted foundational AI assets, including LLMs. |
Gen AI studio | Gen AI studio provides a hands-on environment to interact with models. | Rapidly prototype gen AI applications through the playground. |
233% ROI with Red Hat AI
Red Hat commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Red Hat AI.
After interviewing Red Hat AI customers, the analysis found that a composite organization realized an ROI of 233% over 3 years, representing a total value of more than triple their initial investment.1
Case studies
DenizBank sped up time to market from days to minutes.
The digital media company uses AI to improve viewer experience and grow their audience.
Developers use OpenShift AI to foster AI experimentation.
Airbus Helicopters builds production line integrity with Red Hat OpenShift AI.
AI quickstarts
Explore a variety of innovative AI use cases from our community. These simple, focused examples have been designed for fast and easy deployment on the Red Hat AI platform.
Why choose Red Hat AI?
Build on a trusted foundation that supports any model and any agent on any hardware accelerator—across the hybrid cloud. Red Hat AI gives organizations the freedom to deploy where their data, compliance, and cost requirements demand.
Inference
Manage model complexity with fast, efficient inference powered by vLLM and the control to run any model on any accelerator across the hybrid cloud.
Data
Customize domain-specific agentic AI use cases with models connected to your organization’s own private data.
Agents
Simplify and accelerate your journey to successful agentic AI adoption with governance and control.
Platform
Deploy resilient, trustworthy AI solutions on a foundation of open source transparency and hybrid cloud scalability.
Deploy with partners
Experts and technologies are coming together so our customers can do more with AI. Explore all of the partners working with Red Hat to certify their operability with our solutions.
AI customer stories from Red Hat Summit and AnsibleFest 2025
Turkish Airlines doubled the speed of deployment times with organization-wide data access.
JCCM improved the region's environmental impact assessment (EIA) processes using AI.
Denizbank sped up time to market from days to minutes.
Hitachi operationalized AI across its entire business with Red Hat AI.
Latest Red Hat AI news
How to try Red Hat OpenShift AI
Developer Sandbox
For developers and data scientists who want to experiment with building AI-enabled applications in a preconfigured and flexible environment.
60-day trial
When your organization is ready to evaluate the full capabilities of OpenShift AI, explore them with a 60-day product trial. An existing Red Hat OpenShift cluster is required.
Red Hat AI expertise
Prototype an AI solution, streamline the deployment of your AI platform, or advance your MLOps strategies. No matter your AI goal, Red Hat Consulting can help.
Explore more AI resources
Define your AI strategy with the AI Assessment
Open source: The fast-track to AI success
A blueprint for sovereign AI
Get a guide to MaaS
Contact sales
Talk to a Red Hatter about Red Hat AI
1Forrester Consulting study, commissioned by Red Hat. “Forrester Total Economic Impact™ Of Red Hat AI." February 2026.
