Nutanix, a pioneer in hybrid multicloud computing, announced its new Agentic AI solution. The company introduced a full software stack designed to accelerate enterprise adoption of Agentic AI for business transformation.

As Agentic AI adoption grows, enterprises are reaching a tipping point. However, the challenge is no longer building models or agents. Instead, organizations now face complexity in managing infrastructure required to run thousands of AI agents securely at scale. Therefore, infrastructure and platform teams need better tools to build and operate AI factories while ensuring performance, security, and compliance.

At the same time, developers and data scientists expect seamless access to tools. They want to run and fine-tune models, build agents, and securely connect them to enterprise data.

Thomas Cornely, Executive Vice President of Product Management at Nutanix, explained the shift. He said traditional AI infrastructure focused on running a single large workload. In contrast, production Agentic AI requires handling thousands of services, agents, and users simultaneously. He added that Nutanix Agentic AI extends capabilities across its AHV hypervisor, Flow Virtual Networking, Nutanix Kubernetes Platform, and Nutanix Enterprise AI. As a result, it enables enterprises to build, operate, and govern AI factories more efficiently.

Moreover, the solution integrates with NVIDIA AI Enterprise at the Agent Builder layer. It orchestrates a certified ecosystem of AI factories. This allows enterprises to build, run, and secure agentic AI applications in dynamic, multiuser environments. The platform combines infrastructure orchestration, security software, AI Platform Services, and Models-as-a-Service.

In addition, Nutanix and NVIDIA are collaborating on the foundation for autonomous enterprise agents. This includes integration with the NVIDIA Agent Toolkit and the NVIDIA OpenShell runtime.

The solution also focuses on improving performance, security, and cost efficiency. It reduces complexity and enables predictable token costs.

First, the platform includes Agentic AI services and a Kubernetes-based layer. Nutanix Enterprise AI version 2.6 introduces an AI Gateway for unified policy control across cloud and private large language models. It also adds support for Model Context Protocol servers and fine-tuning capabilities. Furthermore, developers can use NVIDIA Nemotron models to build advanced agentic systems capable of reasoning and executing complex tasks.

Second, Nutanix enhances infrastructure optimization and security. Its AHV hypervisor now supports topology-aware resource allocation for GPU-intensive workloads. Additionally, Flow Virtual Networking offloads network processing to NVIDIA BlueField DPUs. This improves performance while reducing CPU and memory usage. Consequently, enterprises can achieve better resource utilization and lower cost per token.

Third, the platform strengthens data services. Built on the NVIDIA AI Data Platform reference design, Nutanix Unified Storage delivers scalable performance for thousands of GPU clients. It also supports advanced technologies such as S3 over RDMA and NFS over RDMA. This ensures low-latency data access and improved GPU efficiency across AI workloads.

Industry partners highlighted the importance of this development. Analysts noted that the unified stack reduces infrastructure friction. It brings together Models-as-a-Service, Kubernetes platforms, and GPU-aware systems into a cohesive solution.

Meanwhile, partners including NVIDIA, Dell Technologies, Cisco, Lenovo, TCS, Supermicro, Accenture, and Fujitsu emphasized scalability and performance. They stated that the solution enables enterprises to move from experimentation to large-scale AI production. They also highlighted improved security, operational simplicity, and faster deployment of AI factories.

Overall, the launch reflects a broader industry shift. Enterprises are moving toward large-scale AI operations that require integrated infrastructure and simplified management. As a result, Nutanix aims to position its platform as a foundation for scalable and efficient Agentic AI adoption.

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