University of Utah Builds Sovereign AI Factory with HPE and NVIDIA

/ Application Development, Governance, Infrastructure

 Full-stack AI infrastructure expands computing capacity threefold, fueling healthcare innovation, academic collaboration, and regional growth

The News

At NVIDIA GTC DC 2025, the University of Utah announced the deployment of a sovereign AI factory developed by Hewlett Packard Enterprise (HPE) and powered by NVIDIA AI Computing by HPE infrastructure to accelerate research, drive healthcare breakthroughs, and support Utah’s broader economic and educational ecosystem.

The initiative, supported by a philanthropic gift from the Huntsman Family Foundation, is part of a statewide push to expand AI infrastructure, attract new businesses, and strengthen Utah’s workforce. The deployment will triple the University’s computing capacity, enabling secure, high-performance AI across healthcare, life sciences, and interdisciplinary research fields.

“This AI factory provides the University of Utah with a fully integrated, sovereign platform for data-intensive research,” said Trish Damkroger, SVP and GM, HPC & AI Infrastructure Solutions at HPE. “We’re proud to partner with NVIDIA to deliver a system that makes data governance core to the mission—combining infrastructure, software, and services for innovation at scale.”

Analyst Take

The University of Utah’s new AI factory shows momentum for sovereign AI adoption within the public sector. Built as a full-stack solution managed through HPE GreenLake, the deployment integrates HPE Cray XD670 servers, NVIDIA Hopper GPUs, advanced cooling, storage, and orchestration software to handle massive, parallelized workloads such as LLM training, multimodal AI, and biomedical data processing.

Unlike conventional public-cloud approaches, this system is sovereign by design, ensuring full control over data, compliance, and intellectual property. This is especially critical in medical and life sciences research, where sensitive data must remain within jurisdictional boundaries.

As Taylor Randall, president of the University of Utah, stated:

“Our goal is ensuring the state is awash in computing power by building a robust and scalable AI ecosystem that benefits our entire higher education system, powers research to find new healthcare cures, and ignites Utah’s entrepreneurial spirit.”

By bringing sovereign AI capabilities into the academic sphere, the University is working to become both a regional AI innovation hub and a national model for how higher education can catalyze digital economies.

AI Factories Become Strategic Economic Engines

The University’s deployment supports a growing trend with AI infrastructure being a strategic economic asset. HPE and NVIDIA’s partnership provides an end-to-end solution by integrating hardware, software, and management through HPE GreenLake’s as-a-service model enabling accelerated time-to-value while maintaining flexibility and security.

At the heart of this system are HPE OpsRamp and HPE Morpheus Enterprise Software, which provide multi-tenant orchestration and centralized observability for managing cloud-native, traditional, and AI workloads. This enables the University to:

  • Streamline operations across hybrid and multicloud environments
  • Support shared research infrastructure for multiple departments
  • Repatriate workloads from public clouds, reducing compute costs by up to two-thirds
  • Enable cross-disciplinary collaboration and rapid deployment of agentic and generative AI workloads

For the physical infrastructure, DataBank was selected as the colocation partner for its ability to manage high-density workloads while maintaining proximity to the University. The colocation facility will also serve as an innovation showcase, a model for regional AI infrastructure that supports both public institutions and private-sector R&D.

Academic AI Factories Extend Beyond Research

Academic institutions increasingly play dual roles through both advancing knowledge and driving local economic transformation. Utah’s AI factory exemplifies how universities can partner with global technology leaders to create sovereign, open, and extensible AI ecosystems that benefit multiple stakeholders including students, businesses, and government alike.

As AI workloads diversify (from LLMs to agentic AI orchestration and real-time digital twins), the university’s platform lays the groundwork for a statewide AI innovation corridor. The combination of AI sovereignty, public-private partnership, and open innovation reflects a model increasingly adopted by nations and states seeking to retain control of data and intellectual property while scaling their research ecosystems.

Looking Ahead

The University of Utah’s sovereign AI factory sets a precedent for academia-driven AI infrastructure, integrating public investment, private expertise, and philanthropic support to fuel both research and economic growth.

As universities, hospitals, and state governments accelerate AI adoption, sovereign AI factories could become a new template for balancing innovation with compliance. Expect more higher-education institutions to follow this model, establishing regional AI hubs that connect education, healthcare, and entrepreneurship.

The next evolution will likely involve AI workload federation across multiple sovereign sites, linking compute, data, and research workflows nationwide while maintaining privacy and compliance.

Key Takeaways

  • The University of Utah deploys a sovereign AI factory developed by HPE and NVIDIA, tripling its computing capacity.
  • Managed through HPE GreenLake, the system integrates Cray XD670 servers, Hopper GPUs, and full-stack orchestration.
  • Designed for data sovereignty, the platform ensures compliance and security for healthcare and life sciences research.
  • OpsRamp and Morpheus Enterprise Software enable shared, multi-tenant research and multicloud governance.
  • The initiative supports Utah’s broader economic development goals, aligning education, research, and industry innovation.

Author

  • Paul Nashawaty

    Paul Nashawaty, Practice Leader and Lead Principal Analyst, specializes in application modernization across build, release and operations. With a wealth of expertise in digital transformation initiatives spanning front-end and back-end systems, he also possesses comprehensive knowledge of the underlying infrastructure ecosystem crucial for supporting modernization endeavors. With over 25 years of experience, Paul has a proven track record in implementing effective go-to-market strategies, including the identification of new market channels, the growth and cultivation of partner ecosystems, and the successful execution of strategic plans resulting in positive business outcomes for his clients.

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