Launches Early Access To Managed AI Platform, the operating system for artificial intelligence (AI) and machine learning (ML) built by data scientists, announced the exclusive early release of the Metacloud, a new managed service enabling AI developers full flexibility to run AI/ML workloads on a mix of infrastructure and hardware choices, even within the same AI/ML workflow or pipeline. Available platform integrations include Intel, AWS, Azure, GCP, Dell, Redhat, VMWare, Seagate and more.

Many AI projects are stalled due to the inability of the existing IT infrastructure (either in the cloud or on-prem) to meet the growing demands of AI workloads. AI developers are often locked into one infrastructure architecture, giving them little flexibility to try new and exciting ML/AI infrastructure options.

To experiment with new environments, data scientists need to re-instrument an utterly new stack that might take months to set up. AI developers need the ability to choose the best of breed compute and cloud solution for each workload, based on each architecture’s cost/performance trade-offs, instantly, without the burden of a long-term commercial commitment.

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With the early release of Metacloud, AI developers now have the full flexibility and choice to run any AI architecture for any AI workload on-demand. With the end to end operating system for machine learning, AI developers can now manage data, develop, train, and deploy models on any infrastructure instantly. Metacloud introduces a new flexible interface for running AI workloads instantly: BYOC (Bring Your Own Computer) and BYOS (Bring your Own Storage) by delivering a developer-friendly portal to set up and launch AI/ML workflows using any hardware or storage service available from a partner menu. Metacloud works with any AI infrastructure provider designed by cloud-native technologies such as containers and Kubernetes. Developers simply create an account, select the AI/ML infrastructure to run their project (any public cloud, on-prem, co-located, dev cloud, pre-release hardware and more) and run the workload.

The Metacloud is provided as part of, a Kubernetes-based full-stack machine learning operating system that includes everything data scientists and developers need to build and deploy AI applications.

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