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Nutanix simplifies production agentic AI with new platform updates

Mohammad Abulhouf, Vice President & GM, Middle East & Africa, Nutanix .
Mohammad Abulhouf, Vice President & GM, Middle East & Africa, Nutanix.

Nutanix has expanded its hybrid cloud offerings with the launch of Nutanix Enterprise AI 2.8 and updates to its Kubernetes Platform. The dual-native architecture allows firms to run AI alongside legacy applications, enhancing security and reducing the need for costly rearchitecting. The update includes new partner incentives and tools like Service Provider Central to support managed AI services.

Many enterprises face a major roadblock when deploying AI: AI is accelerating the shift to containers, while critical applications and data remain spread across both virtualized and containerized environments. This divide can force enterprises to add infrastructure silos, move data or rearchitect existing workloads to support AI alongside the applications and data they already run. Nutanix addresses this with a governed, dual-native architecture that runs traditional applications and modern AI side by side, allowing the infrastructure to flexibly support the workload, integrated with leading silicon partners to provide choice and flexibility to customers. By bringing AI to where enterprise data already lives, Nutanix helps customers reduce silos and accelerate ROI without costly rearchitecting or added networking and data layer complexity.

Expanding on NCP capabilities, NAI and NKP are designed to enable organizations to securely run, manage, and govern AI, containerized applications and virtualized workloads through a consistent control plane. These complement the core platform capabilities for near-bare metal performance for AI on virtualized infrastructure introduced with NCI 7.6. Together, they give enterprises a flexible alternative to infrastructure stacks that limit architectural choice, drive up costs, and require disruptive platform changes.

For partners, the new Powered by Nutanix: Verified Services program aims to enable them to capitalize on major industry shifts and next-generation AI deployments by empowering them to build validated, high-margin services practices that span the full customer lifecycle. To operationalize these flexible new offerings, Service Provider (SP) Central provides an adaptable multitenant cloud foundation, giving service providers the control they need to grow infrastructure, platform, cloud-native, and AI services on their own terms.

“Enterprise AI should not require customers to rebuild the systems that already run their business,” said Thomas Cornely, Executive Vice President, Product Management, Nutanix. “With our dual-native architecture, customers can bring AI to their existing applications and data while running each workload on the infrastructure best suited to it, with consistent operations and governance across VMs, containers and AI. This gives organizations a practical path to production without creating new silos or limiting future choice.”

Nutanix Enterprise AI: Helping Enterprises Bring AI to Their Data Without Rebuilding Everything

NAI delivers a unified and secure platform to deploy, manage, and scale AI workloads across hybrid environments. It enables enterprises to enforce governance over their agents and models, gain total visibility over token usage, and streamline AI development with a simple interface with built-in observability metrics and easy to use model-as-a-service while ensuring security, scalability, and integration with existing infrastructure.

Key NAI updates include:

  • Agent Gateway: This now includes a generally available MCP Gateway which serves as a secure, unified front door for AI agents to access tools and data without custom engineering. To complement this, Nutanix has also released MCP Server for NCP to help customers build agentic AI applications with secure access to the infrastructure managed by Nutanix.
  • Private Inference: New advanced inference and fine tuning capabilities enable scalable, multiGPU inference for LLMs via tensor parallelism, delivering high-throughput serving and low-latency response times for enterprise LLM workloads. In addition, this enables batch inference and speculative decoding. Key features include: 1) Parameter-Efficient Fine-Tuning which supports Low-Rank Adaptation (LoRA) fine-tuning for smaller models (<8B parameters), helping organizations to cost-effectively customize open LLMs on private domain data using single-GPU compute while seamlessly deploying adapters straight to serving pipelines; 2) Scalable multiGPU serving which enables high-throughput multiGPU inference via tensor parallelism, delivering fast, distributed serving across enterprise hybrid cloud environments; and 3) Speculative decoding which accelerates LLM inference token generation by up to 2.5x using lightweight draft models, cutting output latency without sacrificing model accuracy.
  • Enhanced Security against Rogue AI: With the rise of agentic AI and the risk of models breaking out of sandboxes, security is paramount. NAI provides robust protection against rogue models through our platform and APIs, featuring fine-grained Identity and Access Management (IAM), custom roles and seamless model sharing. This enforces least-privilege security, helping ensure agents operate securely and restricting access to only authorized roles, as well as support for air-gapped NVIDIA NIM deployment.

Mohammad Abulhouf, Vice President & GM, Middle East & Africa, Nutanix commented: “Across the Middle East and Africa, organizations are moving rapidly from AI experimentation to deploying AI in mission-critical environments. As this transition accelerates, enterprises need more than powerful AI models—they need the flexibility to run AI alongside the applications and data that already underpin their businesses, while maintaining the security, governance and control required in their respective markets. Nutanix’s dual-native approach addresses this reality by helping organizations bring AI closer to their data and existing workloads, without forcing disruptive infrastructure changes. This gives enterprises across the region a practical path to scale AI responsibly and turn innovation into measurable business value.”

Nutanix Kubernetes Platform: A Trusted, Production-Ready Foundation for Modern Apps and AI

With NKP, organizations can simplify container operations across containers running on bare metal and VMs without piecing together complex, custom stacks. The upcoming release will provide an AI-optimized platform for building and running agentic applications at scale, including the following features coming soon:

  • NKP Metal: Built to bring HCI-grade simplicity to bare-metal Kubernetes, with automated OS, firmware, and container deployment, and persistent, enterprise-grade storage natively, eliminating the complexity of patchwork platforms.
  • NKP Full Stack: While NKP Metal is intended to bring simplicity to bare-metal deployments, NKP on AHV remains the cornerstone for organizations requiring robust, agile virtualized environments. Combined with Nutanix Flow, NKP on AHV is designed to deliver stronger network-level sandboxing for AI agents, helping provide essential isolation to mitigate the risk of rogue attacks and lateral movement.
  • AI Applications Catalog: Offers a one-click deployment path for curated, validated AI/ML software (Kubeflow, Milvus, Slurm) to help bypass manual integration challenges.
  • Hardware and Compliance: Planned expansion of ecosystem support with validated GPU integrations, alongside dynamic resource allocation for modern AI workloads.

CNCF Certified Kubernetes AI Conformant Platform: NKP has attained formal CNCF certification to validate that NKP provides the standardized APIs and capabilities required to reliably operate enterprise AI workloads.

AI Storage Performance and Validated Certifications with NVIDIA

Demanding AI workloads require infrastructure that keeps data moving, maximizes GPU utilization, and reduces deployment risk. Nutanix Unified Storage (NUS) recently achieved NVIDIA-Certified Storage validation at the enterprise level, providing a trusted, interoperable foundation that helps eliminate data bottlenecks. NUS establishes a low-latency, high-throughput data path directly to GPUs, maximizing GPU utilization and ensuring linear scalability for large-scale production AI workloads.

Helping Partners Build, Monetize and Grow AI Services

According to Gartner®, “By 2029, 55 percent of enterprises will migrate 100 percent of workloads from VMware to alternative infrastructure delivery solutions”#. To help partners capitalize on this market shift, next-generation AI deployments and other emerging opportunities, Nutanix recently launched the Powered by Nutanix: Verified Services program. This program provides the framework to support the broader partner ecosystem in transitioning from traditional, one-time deals to high-margin, recurring revenue streams by building validated services practices. Backed by streamlined onboarding, comprehensive service delivery kits, and exclusive badging across hybrid cloud infrastructure, Kubernetes, and VM migration, the program equips partners to own the full customer lifecycle, drive faster time-to-value, and maximize long-term retention.

Nutanix is also announcing the general availability of SP Central, a unified multitenant control plane that gives displaced VMware service provider partners greater choice in how they build and monetize services. Service Provider Central gives providers one consistent foundation to build and monetize a broad portfolio of infrastructure, application, cloud-native, and AI services, with the flexibility on deployment location and licensing they need. This is designed to help providers improve utilization and protect margins while giving customers more choice in how and where they run applications and AI workloads.

“As enterprises deploy agentic AI to automate complex workflows, they need infrastructure that delivers the performance, security and control required for production environments. Cisco is bringing that foundation. Together with Nutanix’s governed, dual-native cloud operating model, we’re giving organizations greater choice in how they deploy and operate AI while maintaining the control they need across their environment.”
Jeremy Foster, Cisco GM & SVP, Cisco Compute

“At Continent 8 Technologies, we’ve worked closely alongside Nutanix to help shape the next generation of cloud services for regulated industries. Our continued collaboration with Nutanix, including the development of Service Provider Central, is built around helping our customers adopt modern cloud and AI capabilities without adding unnecessary complexity. Together, we’re enabling organizations in highly regulated industries to innovate faster and focus on their core business, while maintaining the security, compliance, and operational control they require.” Edward O’Connor, Chief Technology Officer at Continent 8 Technologies

“The rise of agentic AI is redefining how AI services are delivered, making security and sovereignty foundational requirements. Through our collaboration with Nutanix, we are enabling enterprises and service providers to build high-performance, multitenant AI platforms with hardware-enforced isolation and security. This ensures that sensitive data and models remain protected in use, delivering the secure scale and efficiency required for next-generation AI factories.” Bill Pearson, VP, Data Center Software, Intel

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