From Vision to Reality: AI Factory Solutions for Government and Enterprise

AI factories are transforming how governments and enterprises operate—unlocking new levels of automation, intelligence, and efficiency. From streamlining citizen services to accelerating innovation in regulated industries, AI is no longer a future vision—it’s today’s imperative.

The Challenges of Building AI Factories

Despite the promise, building and operating AI factories is complex. Organizations face hurdles like fragmented infrastructure, a very fast rate of change of hardware and software stacks (including models), heterogeneous GPU and CPU generations, and the need for scalable, secure environments. Add to that the need to manage demands from a variety of sources within the organization, all with their varying levels of security and performance needs and levels of separation from other entities. These challenges can slow deployment, increase costs, and introduce risk—especially when managing complex and sensitive workloads like agentic AI.

Nutanix: A Foundational Software Platform for AI Factories

Nutanix plays a critical role in enabling AI factories by providing a secure, scalable, and efficient software platform that enables organizations to easily create shared inference services using the Nutanix Enterprise AI (NAI) solution to meet the diverse AI needs of the organization, providing freedom of choice of models as well as underlying hardware. In addition, the Nutanix Kubernetes Platform (NKP) solution provides a production-grade Kubernetes® base without the complexity of managing each individual component of the stack that otherwise makes running Kubernetes difficult.  The Nutanix platform complements the AI factory solutions offered by various hardware vendors based on NVIDIA Enterprise Reference Architectures.

Added Challenges for Government and Security-Conscious Organizations

For government agencies and security-sensitive enterprises, the bar is even higher. Data privacy regulations, compliance with standards like FIPS encryption, and the need for sovereign control over infrastructure and data create additional layers of complexity. According to a 2025 US Government Accountability Office (GAO) report, 10 out of 12 federal agencies cited policy and compliance as major barriers to AI adoption¹.

To meet these challenges, NVIDIA introduced the AI Factory for Government reference design—a full-stack AI architecture tailored for deploying AI workloads in high-assurance environments—provides a blueprint for meeting these challenges. Built on the NVIDIA Blackwell architecture, it integrates NVIDIA-Certified Systems, NVIDIA Networking, and NVIDIA AI Enterprise software, along with government-ready containers and open models like NVIDIA Nemotron. 

NVIDIA’s government-ready containers have been tested to run reliably on NKP and interoperate with NAI. This provides seamless deployment of the AI Factory for Government using NKP as the Kubernetes base, and NAI to build the shared inference service to operationalize the NVIDIA software components. The joint solution provides consistent performance, simplified operations, and leverages hardened configurations, FIPS encryption, and continuous vulnerability monitoring, making it ideal for regulated environments. NKP can run on virtual machines - often preferred for multi-tenant use cases - or on bare metal servers where there isn't a need for a virtualization layer. Earlier this year, Nutanix announced that NKP will ship Ubuntu Pro as an additional option with NKP Pro and Ultimate licenses for a validated, well-integrated bare metal Kubernetes stack on which to run your AI workloads.

“We’re excited to work with NVIDIA and hardware leaders to deliver a fully integrated, hardened AI factory solution tailored for government needs,” said Thomas Cornely, SVP of Product Management at Nutanix. “With built-in FIPS-compliant encryption across every layer, we’re helping organizations protect sensitive data while accelerating AI adoption. By leveraging NKP and NAI, customers gain robust governance features—like fine-grained access controls, auditing, API token management, and full infrastructure visibility—enabling a fast time to first token, cost control , and the robust security for mission-critical AI workloads.”

Server OEMs + NVIDIA + Nutanix = Complete AI Factory Solutions

Together with leading hardware OEMs, NVIDIA, and Nutanix deliver complete AI factory solutions for enterprises and governments. These solutions incorporate NVIDIA AI architecture for accelerated computing, NKP for simplifying the Kubernetes layer, and NAI for scalable inference management, enabling organizations to scale AI workloads across on-premises and hybrid cloud environments. The enhanced security and encryption technology included in the AI Factory for Government reference design spans all the components of the joint solution, including NKP.  The flexible design supports future growth without model or deployment mode lock-in. It adapts easily to evolving use cases, from law enforcement and healthcare to financial management and national security.

"Enterprises and government agencies are seeking secure, scalable AI architectures to streamline operations and solve challenges that demand both flexibility and compliance,” said Justin Boitano, vice president, enterprise AI products, NVIDIA.  “Together, NVIDIA and Nutanix are enabling organizations to confidently deploy AI factories that accelerate innovation while meeting the highest security and regulatory standards."

By combining NVIDIA AI Factory for Government reference design, Nutanix’s robust software platform, and hardware with NVIDIA AI architecture, governments and enterprises can confidently deploy scalable, secure AI solutions. This joint approach accelerates time-to-value, reduces complexity, and ensures compliance—empowering organizations to harness the full potential of AI.

To read about the Nutanix integration with the Cisco Secure AI Factory or the Dell AI Factory, read the Cisco press release and the Dell blog. 

¹Artificial Intelligence: Generative AI Use and Management at Federal Agencies, GAO-25-107653. Published: Jul 29, 2025. Publicly Released: Jul 29, 2025.

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