Nutanix, a hybrid multicloud computing company, recently launched a new agentic AI solution to help customers boost agentic AI adoption for business transformation.
Nutanix brings AI factory enablement stack to market
The full software stack, Nutanix Agentic AI, is designed to help infrastructure and platform teams build and operate AI factories, while providing shared access to their resources and maximizing performance, security, and compliance with sovereignty requirements.
Data scientists and developers get easy access to tools and services for running and fine-tuning models, building agents, and securely connecting them to enterprise data.
NVIDIA integrations and corporate partnerships build a foundation for agentic AI
The Nutanix Agentic AI solution integrates with NVIDIA AI Enterprise at the Agent Builder layer and orchestrates the NVIDIA-certified AI factory ecosystem for supported configurations.
It also enables customers to build, run, and protect agentic AI applications in dynamic, multi-user AI environments with a full suite of infrastructure orchestration and security software – along with AI Platform Services (PaaS) and Models-as-a-Service (MaaS) for data scientists and Agentic AI developers.
Additionally, Nutanix and NVIDIA are working together to lay the foundation for autonomous agents in the enterprise through integration with the NVIDIA Agent Toolkit, including the NVIDIA OpenShell open-source runtime.
Reducing complexity and reducing costs: capabilities overview
The solution reduces complexity, delivers optimized performance and security, and enables lower, more predictable token costs. Among the features are:
- Agentic AI Services and a Kubernetes Platform with a native software layer consisting of:
- An advanced AI gateway and MaaS: With the latest release of Nutanix Enterprise AI (NAI) version 2.6, the AI Gateway service will now provide unified policy control for cloud-hosted and private LLMs. It features new support for the Model Context Protocol (MCP) server, and Fine Tuning extends existing MaaS capabilities to enable agents to securely connect to enterprise tools and data sources. NAI now includes support for the NVIDIA Nemotron family of open-source AI models, datasets, and training tools for building agentic AI systems to reason, securely access tools, and complete complex multistep tasks independently.
- An open Kubernetes Platform with a rich AI catalog: Nutanix is simplifying the path to agentic AI by extending its CNCF-compliant Nutanix Kubernetes Platform with a rich catalog of pre-built open source AI developer tools including Notebooks, Vector Databases, MLOps workflow engines, and Agentic frameworks. Full integration with NVIDIA AI Enterprise software enables developers to instantly deploy NVIDIA NIM microservices, including Nemotron, accelerating the development of high-performance AI applications in production.
- Foundational data services for AI: Nutanix Unified Storage, built on the NVIDIA AI Data Platform, delivers linearly scalable read/write performance for thousands of GPU clients. Nutanix provides a scalable, low-latency data fabric to maximize GPU efficiency across all enterprise AI workloads by providing a high-capacity tier for KV Cache offloading and support for S3 over RDMA and NFS over RDMA.
“Contrary to AI infrastructure for model training that was optimized for run ‘one big job,’ production Agentic AI infrastructure needs to handle scale and high rates of changes for thousands of AI services, agents, and concurrent users and developers,” said Thomas Cornely, executive vice president of product management at Nutanix.
“Nutanix Agentic AI extends our AHV hypervisor, Flow Virtual Networking, Nutanix Kubernetes Platform, and Nutanix Enterprise AI to deliver a cloud operating model to enterprise AI factories, enabling infrastructure and platform teams to simply build, operate, and govern AI factories while providing Agentic AI developers with the performance and rich set of models and AI platform services they need,” Cornely continued.
Nutanix recently released its latest Enterprise Cloud Index, which found that AI adoption is accelerating container use while exposing infrastructure gaps. Read more about the Index and how AI is driving container adoption.