Red Hat AI on IBM Cloud

Accelerate your AI and hybrid cloud strategy with a secure, scalable and open platform built by IBM and Red Hat. 

Scalable. AI-Ready. Open. Flexible.

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AI-ready solutions from Red Hat and IBM Cloud

Red Hat® AI on IBM Cloud® provides a consistent and secure way to build, train, customize and deploy AI and machine learning workloads across hybrid cloud environments. The portfolio combines open source innovation with enterprise-grade cloud infrastructure, helping IT teams reduce operational complexity and accelerate AI adoption. This portfolio is designed for organizations that need reliable AI infrastructure and a faster path from prototype to production.

Customization

Customize models with your own enterprise data.

AI workloads

Deploy AI workloads on a consistent hybrid cloud platform.

GPU-optimized

Scale training and inference with GPU‑optimized infrastructure.

Governance

Apply security, governance and compliance across environments.

Red Hat AI offerings solutions on IBM Cloud

One open, hybrid, enterprise-grade AI platform. Three solutions.

Go deeper on our Red Hat AI on IBM Cloud Solution Brief

Build, deploy and manage AI applications at scale

OpenShift AI on IBM Cloud brings Red Hat® OpenShift® together with integrated MLOps and generative AI tools. It gives you a consistent, Kubernetes-based platform to manage AI workloads across hybrid cloud environments.

Key capabilities:

  • Optimized infrastructure for AI training and inference

  • Integrated pipelines for end‑to‑end model lifecycle management

  • GPU‑enabled compute options with intelligent autoscaling

  • Enterprise‑grade security, compliance and observability

  • Unified support delivered jointly by IBM and Red Hat

OpenShift AI provides a reliable and secure foundation for AI operations and production deployment.

A secure, high-performance operating system for AI workloads

Red Hat Enterprise Linux AI (RHEL AI) offers a stable environment to run and customize LLMs across cloud, data center and edge locations. It includes the open source Granite® model family and InstructLab tools, giving teams a ready-to-use AI development and deployment environment.

Key capabilities:

  • Enterprise security and lifecycle management
  • Optimized support for GPUs and AI accelerators
  • Portable deployments across hybrid cloud
  • Consistent operations aligned with standard RHEL processes

RHEL AI provides a secure and predictable foundation for enterprise AI workloads.

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Customize enterprise AI models with a managed service

Red Hat AI InstructLab™ on IBM Cloud is a fully managed service that enables you to customize large language models without requiring full retraining. It uses synthetic instruction generation to add new behaviors, skills and domain knowledge, helping reduce GPU costs and speed up model development.

Key InstructLab capabilities:

  • Model customization with enterprise data
  • Lower infrastructure requirements than traditional fine‑tuning
  • Secure IBM Cloud environment for data protection
  • Standardized workflows across teams

InstructLab provides a faster way to build AI models that fit your business needs and governance requirements.

Why Red Hat AI on IBM Cloud

Red Hat AI on IBM Cloud provides a secure, consistent and scalable foundation to move AI workloads from pilot to production across your hybrid cloud.

Accelerated AI adoption

Streamlined tools and automated workflows help reduce time to production and simplify model customization.

Hybrid cloud consistency

A unified operating experience across cloud and on-premises environments helps teams deploy and manage AI more reliably.

Enterprise security and compliance

Built‑in controls support data protection, governance and regulatory requirements for sensitive workloads.

Scalable AI infrastructure

GPU‑optimized compute, storage and networking deliver the performance needed for training and inference at scale.

Reliable and accurate AI

High‑quality data, validated models and robust deployment options help improve system accuracy and decision-making.

Lower operational cost

Optimized infrastructure and more efficient model‑customization methods help reduce resource use and overall costs.

Built for protection

Security and privacy controls help to support regulatory needs.

End-to-end AI platform

From servers and storage to orchestration and model lifecycle management, the platform reduces complexity and supports consistent operations.

Case studies

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Happiest Minds
Born digital AI platforms for exponential digital revenue streams.
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Wimbledon
Generative AI further enhances a world-class digital experience.
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IBM Account 360
Transforming collaboration across client-facing teams at IBM.
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US Open
Acing the US Open digital experience.

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