How do you operationalize Generative AI consistently and at scale?

If you’re like me, heck even my kids, you’ve been hearing all the AI hype lately. And I’m sure you’re trying to figure out how it can benefit you. The possibilities seem endless.

But get past all the hype and you’ll see generative AI changes everything about how you can go to market, delight customers, and plan for tomorrow. I think about automating customer support, training HR recruitment models, better sales forecasting, improved marketing content, automating repetitive tasks, and even generating code. And everything in between.

But how do you get there from where you are? Once you’ve established some goals or ideas of where AI should be infused in your organization, you’ll be faced with a foundational question: What is the best platform to help you reach those AI goals quickly, and for the long-term?

Why does your platform matter when bringing in AI? You have lots of choices when it comes to AI; where the data is stored, how are your data scientists testing models, what types of hardware acceleration is required and where, and with what tools, are the applications developed. AI has big demands on an organization’s resources. And those demands are met only when fully realizing the breadth and depth available in a trusted hybrid cloud strategy.

Red Hat OpenShift AI is an open hybrid AI/ML platform with tools to build, deploy, and manage foundation models, predictive models, and AI-enabled applications. It’s built using open source technologies and provides trusted, operationally consistent capabilities for teams to train, tune, serve models, and deliver new apps that bring in the best of AI capabilities. For consistency, you can choose where you develop and deploy your models, regardless of where they’re running; on-premise, the public cloud, or even at the edge. This deployment flexibility is ideal since generative AI accelerates your move to the cloud and drives your application modernization efforts.

Most organizations  struggle to incorporate AI into their business because of a lack of in-house knowledge to extend an application platform with AI capabilities, the need for a platform to support their new AI/ML implementations, as well as the time and space to “figure it all out.”

This is where a fully managed application platform can take most of the application modernization load off your team and help you accelerate AI application development.

How does a managed application platform  help you?

Self-managed Red Hat OpenShift AI supported on Azure Red Hat OpenShift, allows users to quickly train and test their generative AI models without waiting for infrastructure provisioning. Deploying on a managed platform takes the operational burden off of internal teams and provides more time to focus on enabling new technologies like generative AI.  Additionally, a huge benefit of OpenShift AI is that you’re delivering AI solutions securely and at scale using the SAME OpenShift platform you’d use to deploy traditional applications. Which, as we’ve said before, is the same platform and experience regardless of where it’s deployed. This simplifies the development process between traditional and AI applications, between clouds and infrastructure and between models and AI-enabled applications. Simplification on top of simplification.

Azure Red Hat OpenShift is a first party Azure solution that is jointly engineered, managed and supported by both Microsoft and Red Hat. You can deploy fully managed Red Hat OpenShift clusters without worrying about building and managing the infrastructure to run it. Your Azure Red Hat OpenShift clusters are deployed into your Azure subscription and you’ll receive ready access to, and integration with, Azure tools, singular billing, integrated support and access to committed spend, and discount programs.

Azure Red Hat OpenShift, as with all editions of OpenShift, is a comprehensive application platform which means it includes most everything you need to to build, deploy, run, manage and scale your applications out of the box. If you think about the upgrades, lifecycle policy management, patching, security needs and more of EACH tool and service you use on top of Kubernetes, you can pretty easily envision the benefits of a comprehensive application platform and the time, savings and peace of mind you gain. 

Consistency anywhere.

One of the beauties of OpenShift AI is that you can deploy it anywhere; on premises, in the cloud or at the edge, with the same consistent user experience. This means your team doesn’t have to learn new technologies or processes when deploying in the datacenter, Azure Red Hat OpenShift or anywhere else. There are impactful benefits of hybrid cloud consistency. In fact, a recent study found there to be 50% improved operational efficiency for organizations using Azure Red Hat Openshift. You can read all the details in the Forrester Total Economic Impact of OpenShift cloud services: Azure Red Hat OpenShift spotlight.

Accelerating the AI transition

Nothing tells a better story than hearing it from another organization working through similar objectives.  Ortec Finance, a leading financial services organization, has been using machine learning models on Azure Red Hat OpenShift for over two years for residential housing valuations. They are now also using OpenShift AI to quickly deliver their AI enabled applications.  “This is yet another battery added to the (batteries-included) Azure Red Hat OpenShift platform. Openshift AI will replace our maintenance efforts and proprietary code for the AI model serving in our applications, as OpenShift AI will bring these capabilities with Platform compatibility and support guarantees. Using Openshift AI on Azure Red Hat OpenShift accelerates the transition for the AI enhanced solutions we build in our R&D babs towards our clients,” said Joris Cramwinckel, Chief Technologist at Ortec Finance.

Learn more

Want to learn more about modernizing your AI enabled applications? Click here to take an interactive walkthrough of Azure Red Hat OpenShift and visit our OpenShift AI product page to get started.