Red Hat OpenShift AI enables organizations to develop, train, deploy, and manage artificial intelligence and machine learning models on a consistent, enterprise-ready platform. Built on Kubernetes and integrated with the broader OpenShift ecosystem, OpenShift AI provides a standardized environment where data scientists, developers, and platform teams can collaborate to operationalize AI at scale.
The platform combines familiar data science tools such as Jupyter notebooks with powerful MLOps capabilities for model training, experiment tracking, pipeline automation, and scalable inference. With built-in support for GPUs, distributed workloads, and popular frameworks like PyTorch and TensorFlow, OpenShift AI enables teams to move from experimentation to production without needing to redesign their infrastructure. This makes it easier to operationalize models and integrate AI workloads into existing cloud-native application environments.
Built for hybrid and cloud native AI platforms
OpenShift AI is designed for hybrid and multi-cloud deployments, allowing organizations to run AI workloads consistently across on-premises infrastructure, edge environments, and public clouds. Tight integration with OpenShift provides enterprise-grade security, policy control, and automation, ensuring that AI applications can be deployed and managed with the same governance and reliability as any other business-critical workload.
How ITQ helps
At ITQ, we help organizations build and operate AI platforms based on OpenShift AI that align with their existing cloud-native strategies. From infrastructure design and GPU enablement to MLOps pipelines and model lifecycle management, we guide teams in turning experimental AI projects into reliable, scalable production solutions.
11
Red Hat certificates
1
Golden Kubestronaut
50+
Cloud Native platforms built
200+
Workspace migrations completed
500+
(Sovereign) Data Centers deployed
1.200+
Applications implemented for customers
