AI factories are no longer a distant vision—they are rapidly becoming the operational backbone of modern governments and enterprises. By combining scalable infrastructure, advanced AI models, and enterprise-grade governance, these intelligent systems are transforming how organizations deliver services, make decisions, and innovate securely. In this article, Luke Congdon from Nutanix explores how AI factory solutions, developed in collaboration with NVIDIA and leading hardware partners, are bridging the gap between AI ambition and real-world implementation.
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.
“With Nutanix NKP and NAI, we’re helping customers bring Cisco Secure AI Factory with NVIDIA to life – delivering secure-by-default AI deployments that run on Cisco’s GPU dense servers with NVIDIA AI infrastructure and software. By simplifying Kubernetes and AI lifecycle management, Cisco and Nutanix are helping organizations move from pilot to production faster, and accelerate ROI on their AI investments,”
Jeremy Foster, Senior Vice President and General Manager, Cisco Compute, Cisco
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.
“Through our integration with Nutanix NKP and NAI, we’re delivering a trusted foundation that combines enterprise-grade performance with simplified Kubernetes management. This collaboration enables customers to accelerate their AI innovation with confidence. As part of the Dell AI Factory with NVIDIA, we’re helping enterprises turn AI ambition into operational reality—scaling generative AI responsibly and efficiently across their organizations.”
Varun Chhabra, SVP of Infrastructure Solutions Group and Telecom Marketing at Dell Technologies
“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.
“Lenovo’s Hybrid AI Advantage with NVIDIA helps bring AI to customer data—delivering productivity, agility, and trust. Partnering with Nutanix allows us to offer a complete AI Factory stack in an optimized, hybrid cloud environment —from bare metal to inference. Together, we’re helping customers accelerate AI adoption with confidence and control.”
Scott Tease, VP/GM, Lenovo ISG Product Group
Bio of Author
Luke Congdon is Senior Director of Product Management at Nutanix, where he leads initiatives that simplify enterprise infrastructure for AI and cloud-native applications. With over two decades of experience in cloud platforms, virtualization, and enterprise software, Luke focuses on enabling organizations to operationalize AI securely and efficiently across hybrid environments.
