Red Hat Consulting: Red Hat OpenShift AI Pilot

Leaders in various industries are turning to the power of artificial intelligence and machine learning (AI/ML) to achieve desired business outcomes. Red Hat has the leading open hybrid cloud platform to help organizations train, deploy, and monitor AI/ML workloads and models on-premise and in a public cloud environment.

Even so, deploying these technologies effectively can seem daunting, which makes it all the more important for organizations to use a platform best suited to their needs. Not using the right platform can lead to obstacles—including insufficient access to compute, underused resources, and a lack of knowledge sharing and various versions of libraries—that make it difficult to collaborate and produce quality models at an accelerated pace.

To help address these challenges, Red Hat created Red Hat® OpenShift® AI to provide a unified platform of open source tooling for building, deploying, and managing ML models. Following the release of Red Hat OpenShift AI, a number of customers aimed to expand their data science capabilities but needed help doing so. As a result, Red Hat Consulting introduced the Red Hat OpenShift AI Pilot engagement to help customers identify the tools, integrations, and customizations they need in an AI/ML platform.

Red Hat joined Team Guidehouse to develop new data-driven means of identifying Veterans at risk for suicide. The team used Red Hat OpenShift AI Pilot, a managed cloud service providing a fully supported environment to rapidly develop, train, and test ML models in the public cloud environment before deploying into production. Learn more.

What is Red Hat Consulting: Red Hat OpenShift AI Pilot? 


Red Hat Consulting developed Red Hat OpenShift AI Pilot to focus on helping customers start up their Red Hat OpenShift AI journey and integrate it with their existing enterprise services. With a central platform in place, users will have access to standardized libraries and tools, increased compute availability for all users, and improved onboarding of data scientists and other users.

Through this engagement, Red Hat experts will join an organization’s teams to evaluate the current environment and approach and identify future requirements. They will help deploy and manage Red Hat OpenShift AI and integrate it with other data science tools in customers’ environments to get the most out of the technology.

Red Hat’s tailored approach

Architecture sessions

Red Hat consultants will provide hands-on experience with a focus on deploying to multiple clusters—such as a development, test, and production cluster—and can extend to end users and multiple data science teams.

First, we will get started with architecture sessions to help identify any critical integration points in existing systems and additional tooling needed to meet each customer's unique requirements. Customers can expect Red Hat Consulting to aid in the selection of tools required for their AI/ML platform. Red Hat Consulting will also perform an architecture review to understand their environment and determine how Red Hat OpenShift AI will be used and adopted.

Team collaboration

Following these architecture sessions, Red Hat consultants will collaborate with teams to assist in performing the deployment and configuration of third-party tooling components defined in the architecture design sessions. In this phase, customers will probably experience:

  • Red Hat consultants work with you to appropriately size configurations, integrate with data systems, and configure hardware accelerators, such as GPUs.
  • Assistance in the deployment, configuration, and integration of third-party tooling.
  • If necessary, integrating existing OpenShift functionality (e.g., serverless, GitOps, pipelines) to support platform requirements.


Red Hat acknowledges every customer has different business objectives, so we customize components of the engagement, based on the architecture design sessions, with a focus on:

  • Developing custom pipelines for model training and data integration.
  • Creating pipelines to deliver custom notebooks.
  • Configuring model mesh with custom runtimes.

Red Hat prioritizes helping to bridge the cluster administration, infrastructure teams and data scientists as part of a core foundation of this engagement. Red Hat will work directly with both organizations to help support teams for success to maintain the current state and lay the groundwork for future requirements.

After establishing the pilot, Red Hat will work directly with data scientists to help onboard them and provide customizations to help improve their user experience.


The engagement is predicated on having an appropriately sized OpenShift cluster. Red Hat Services can both help scope and deliver such a cluster as a prerequisite. Red Hat OpenShift AI Pilot does not require you to have any functioning ML models for this engagement, and Red Hat is happy to meet you wherever your team is on your data science journey.

For customers looking to move beyond model experimentation and develop strategies for deploying models to production, Red Hat Consulting: MLOps Foundation is a great follow-up engagement to Red Hat OpenShift AI Pilot.

Getting started with Red Hat Services

Red Hat strives to help our customers to not only deliver their first ML model but the foundation for all of their ML systems. By creating a reusable pattern to train and deploy a ML model as a production-ready solution, Red Hat seeks to help our customers succeed in delivering future ML projects.

Red Hat Services can help to provision data science projects, accelerate the building, training, testing, deploying and monitoring of ML models and consistently export models to production across hybrid cloud and edge environments—from cloud based clusters to fully disconnected on-premise environments.

The Red Hat Services difference

Red Hat Services consist of Red Hat Consulting, Red Hat Training and Certification, and Red Hat Technical Account Management (TAM) and provide customers with comprehensive support and guidance for building modern cloud applications.

Consulting: With hands-on mentoring, Red Hat consultants build skills and encourage independence while also streamlining processes, aligning teams, and ensuring systems and applications work together.

Training: This helps to close skills gaps and hone teams’ Red Hat product expertise by developing role-based, hands-on knowledge in emerging and foundational open source technologies.

Red Hat TAMs: TAMs partner with organizations to resolve potential problems before they occur, minimizing disruption and alleviating time to focus on key business challenges.

Interested in AI/ML services offered by Red Hat? Speak to your Red Hat Account team, or speak to a consultant