Nutanix Enterprise AI

What it does

Nutanix Enterprise AI is a platform for connecting, governing, and running AI models and agents across a hybrid environment. It takes in cloud-hosted and private LLMs, along with enterprise tools and private data sources reached through MCP access, and routes them through a centralized Agent Gateway and a single inference endpoint. Outputs include model inference, agent deployments, audit trails of MCP requests, and token usage visibility.

People use it to deploy LLMs and agents on infrastructure they control, enforce token rate limits, and manage user access through role-based controls. Its distinguishing feature is pairing governance and cost tracking with self-hosted inference, so teams can monitor token consumption and compare usage across deployments. The pages describe support for edge, core, cloud, and neocloud environments and any CNCF Kubernetes platform.

It suits enterprise teams deploying AI in hybrid environments. Nutanix offers a test drive as an evaluation route. The platform supports CNCF Kubernetes environments, so confirm your Kubernetes version, compute requirements, model support, and integration design before deployment. Agree on licensing and commercial terms with Nutanix; a requirement to buy an entire Nutanix infrastructure stack is not assumed.

What it can do

• Centralized Agent Gateway that connects agents to enterprise tools and private data via MCP access with a full request audit trail
• Single secure inference endpoint unifying cloud-hosted models and private LLMs across multiple providers
• Token usage tracking and rate limits to control AI costs
• Role-based access controls and audit trails for users and actions
• Model and agent deployment, user management, and performance monitoring from one dashboard
• Deployment on any CNCF Kubernetes platform, including Nutanix Kubernetes Platform, across edge, core, cloud, and neocloud

Works with

• AMD
• NVIDIA
• Intel
• Cisco

Before you choose

• Designed around Nutanix infrastructure and Kubernetes; adoption assumes that stack.
• Self-hosting models shifts compute and hardware responsibility to the customer; the pages do not give hardware requirements.
• Pricing and purchase terms are not published on the provider’s documentation; confirm before planning budgets.

Listed under

• Coding
• MCP and agent tools

Get started

The page links to a test drive for deploying LLMs and secure APIs on the platform.

1. Review the Nutanix Enterprise AI design reference for the NAI and NKP deployment pattern.
2. Deploy the platform on a supported Kubernetes environment, such as Nutanix Kubernetes Platform.
3. Connect models and providers through the Agent Gateway and configure token rate limits and role-based access.

Commercial terms depend on the agreed deployment and licensing scope. A test drive is available for evaluation.

We couldn’t find published prices for Nutanix Enterprise AI.

Sources for this overview

Product pages, documentation, and pricing checked 30 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Nutanix AI Factory: Deploy Enterprise AI at Scale, No Lock-in ↗www.nutanix.com
• Solutions Architecture | Nutanix / tech center ↗www.nutanix.com

Company website

nutanix.com: product, pricing and policy pages

Web search

Confirms the official site

Social accounts

Accounts the company links, and its posts on X

Human review

Checked by a person

knowledge_base

manual_review

Last checked 30 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.