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Red Hat OpenShift AI

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What is Red Hat OpenShift AI?

Red Hat® OpenShift® AI is a flexible, scalable artificial intelligence (AI) and machine learning (ML) platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid cloud environments.

Built using open source technologies, OpenShift AI provides trusted, operationally consistent capabilities for teams to experiment, serve models, and deliver innovative apps.

Launch AI faster in any environment. Video duration: 5:26

Illustration of a figure using AI/ML interfaces

Bring AI-enabled apps to production faster

Combine the proven capabilities of Red Hat OpenShift AI and Red Hat OpenShift in a single enterprise-ready AI application platform that brings teams together. Data scientists, engineers, and app developers can collaborate in a single destination that promotes consistency, security, and scalability.

OpenShift AI enables data acquisition and preparation, model training and fine-tuning, model serving and model monitoring, and hardware acceleration. With an open ecosystem of hardware and software partners, OpenShift AI delivers the flexibility you need for your specific use cases.

The latest release of Red Hat OpenShift AI provides greater scalability, bias and drift detection, better access to accelerators, and a centralized registry to share, deploy, and track models. This will help accelerate enterprises’ AI/ML innovation and operational consistency at scale across public clouds, datacenters, and edge environments. 

Features & benefits

Less time managing AI infrastructure

Provide your teams with on-demand access to resources, so they can focus on exploring data and building apps that add real value to your organization. Additional time-saving benefits include built-in security and operator life cycle integration.

Tested and supported AI/ML tooling

Red Hat tracks, integrates, tests, and supports common AI/ML tooling and model serving on our Red Hat OpenShift application platform, so you don’t have to. OpenShift AI draws from years of incubation in Red Hat’s Open Data Hub community project and open source projects like Kubeflow.

Flexibility across the hybrid cloud

Offered as either self-managed software or as a fully managed cloud service on top of OpenShift, Red Hat OpenShift AI provides a secure and flexible platform that gives you the choice of where you develop and deploy your models–whether on-premise, the public cloud, or even at the edge.

Leverage our best practices

Red Hat Consulting provides services that allow you to install, configure and use Red Hat OpenShift AI to its fullest extent.

Whether you’re pursuing an OpenShift AI pilot experience or need guidance on building your MLOps foundation, Red Hat Consulting will provide support and mentorship.

Red Hat Enterprise Linux AI

Red Hat® Enterprise Linux® AI is a foundation model platform used to seamlessly develop, test, and run Granite family large language models (LLMs) for enterprise applications.

Partnerships

Get more from the Red Hat OpenShift AI platform by extending it with other integrated services and products.

NVIDIA logo

NVIDIA and Red Hat offer customers a scalable platform that accelerates a diverse range of AI use cases with unparalleled flexibility.

Intel logo

Intel® and Red Hat help organizations accelerate AI adoption and rapidly operationalize their AI/ML models.

IBM logo

IBM and Red Hat provide open source innovation to accelerate AI development, including through IBM watsonx.aiTM, an enterprise-ready AI studio for AI builders. 

Starburst logo

Starburst Enterprise and Red Hat support better and more timely insights through rapid data analysis across multiple disparate and distributed data platforms.

Expand your AI capabilities with IBM watsonx.ai

Red Hat OpenShift AI provides the open source foundation for IBM watson.ai, which provides additional gen AI capabilities.

Collaborating through Jupyter notebooks-as-a-service

Provide pre-built or customized cluster images to your data scientists to build models using Jupyter notebooks. Red Hat OpenShift AI tracks changes to Jupyter, TensorFlow, and PyTorch, and other open source AI technologies.

Screenshot of OpenShift AI console enabled applications tab
Screenshot of OpenShift AI console model serving table

Scaling Model Serving with Red Hat OpenShift AI

Models can be served for integration into intelligent applications on-premise, in the public cloud or at the edge. These models can be rebuilt, redeployed, and monitored based on changes to the source notebook.

Solution Pattern

Red Hat AI applications with NVIDIA AI Enterprise

Create a RAG application

Red Hat OpenShift AI is a platform for building data science projects and serving AI-enabled applications. You can integrate all the tools you need to support retrieval-augmented generation (RAG), a method for getting AI answers from your own reference documents. When you connect OpenShift AI with NVIDIA AI Enterprise, you can experiment with large language models (LLMs) to find the optimal model for your application.

Build a pipeline for documents

To make use of RAG, you first need to ingest your documents into a vector database. In our example app, we embed a set of product documents in a Redis database. Since these documents change frequently, we can create a pipeline for this process that we’ll run periodically, so we always have the latest versions of the documents.

Browse the LLM catalog

NVIDIA AI Enterprise gives you access to a catalog of different LLMs, so you can try different choices and select the model that delivers the best results. The models are hosted in the NVIDIA API catalog. Once you’ve set up an API token, you can deploy a model using the NVIDIA NIM model serving platform directly from OpenShift AI.

Choose the right model

As you test different LLMs, your users can rate each generated response. You can set up a Grafana monitoring dashboard to compare the ratings, as well as latency and response time for each model. Then you can use that data to choose the best LLM to use in production.

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An architecture diagram shows an application built using Red Hat OpenShift AI and NVIDIA AI Enterprise. Components include OpenShift GitOps for connecting to GitHub and handling DevOps interactions, Grafana for monitoring, OpenShift AI for data science, Redis as a vector database, and Quay as an image registry. These components all flow to the app frontend and backend. These components are built on Red Hat OpenShift AI, with an integration with ai.nvidia.com.

Explore related resources

Video

Demo of Red Hat OpenShift AI

E-book

Top considerations for building a foundation for generative AI

Analyst material

Omdia report: Building a strong operational foundation for AI

Checklist

Top 5 ways to implement MLOps successfully in your organization

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.

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