Move from production to operating at scale with control over token cost, data sovereignty, and operations so agentic AI runs efficiently and securely.
The AI Race is No Longer Experimentation
AI is moving from production to operating in real-world environments. What worked in controlled experiments starts to break at scale.
Agentic AI Changes Everything
Rise of autonomous AI agents dramatically increases AI activity, creating new demands for governance, observability, operational consistency, and infrastructure flexibility.
AI Economics Are Under Pressure
Token costs, inference scaling, model sprawl, and cloud unpredictability are forcing organizations to rethink AI operating models.
Data Gravity and Governance Matter
AI depends on enterprise data, making security, access, and compliance critical as usage grows.
AI Creates Operational Complexity
Running AI requires managing models, data, GPUs, and infrastructure across multiple systems and environments.
AI is Becoming Core Infrastructure
AI is rapidly embedding itself into applications, workflows, requiring agent and inference infrastructure on accelerated computing.
What Enterprises Need to Operationalize Agentic AI
Legacy infrastructure cannot support autonomous AI systems at enterprise scale. Operationalizing AI requires a new architecture designed for operational freedom, predictable AI economics, strict data protection, and distributed sovereignty.
Cost and Performance Efficiency
Control AI token cost and optimize performance with efficient infrastructure utilization and token-optimized inference.
Governance and Control Everywhere
Apply consistent governance, security, and policy controls across distributed AI environments.
Unified AI Operations
Standardize how AI runs across infrastructure, data, and applications with consistent operations across environments.
Flexibility Without Lock-In
Run AI across models, infrastructure, and environments without being tied to a single vendor or deployment model.
Nutanix Transforms AI Factories into AI Cloud to Accelerate Agentic AI Adoption
Nutanix delivers a cloud operating model for AI factories with a centralized control plane that governs how agentic AI runs across apps, models, and infrastructure, bringing control to cost, access, and operations in production.
Accelerate AI development and deployment with an integrated AI platform.
Speed Agentic AI development with a ready catalog of AI services
Kick-start your AI programs without waiting for GPUs
Govern AI Consistently
Apply unified governance, security, and sovereignty controls across distributed AI operations.
Agent Gateway for centralized control plane governing agents, tools, and models
Data sovereignty, compliance, and security enforcement
Optimize AI infrastructure and operations for production-scale inference and autonomous AI systems.
Token-efficient inference to control AI costs
GPU-optimized infrastructure to maximize utilization
Applications and Agents
Autonomous Agents, Agentic Apps, Physical AI
Public Frontier Models, Private Models, Fine-tuned Models
AI Platform (Nutanix)
Agent Gateway, Private Inferencing, AI Control and Governance
Data Lakes, RAG, Vector DBs, Pipelines
AI Optimized Infrastructure Software (Nutanix)
VM, Containers, Software-defined Networking, Storage
Compute Infrastructure
GPUs, CPUs, DPUs, Networks
Experience Nutanix Enterprise AI with a Test Drive
Get a hands-on guided experience of Nutanix Enterprise AI (NAI) without setup or installation.
An Open Ecosystem for Agentic AI
Agentic AI is evolving too quickly for closed architectures and fragmented infrastructure. Nutanix enables an open AI ecosystem that gives organizations the flexibility to integrate leading AI models, infrastructure, frameworks, and cloud environments without operational lock-in.
Discover a practical blueprint for building, operating, and governing AI systems at scale. Learn how to support thousands of AI agents with the infrastructure, data services, security controls, and operational model required for enterprise AI.
Power International Holding Secures AI Across 400+ Entities
Learn how Power International Holding centralized AI governance and secured sensitive data across continents with Nutanix Enterprise AI.
Related Products and Solutions
Scaling agentic AI introduces significant operational complexity. Enterprises must manage distributed AI infrastructure, GPU-intensive inference workloads, data governance, security, observability, and AI economics across clouds, datacenters, and edge environments. As autonomous agents multiply and interact with enterprise systems, maintaining operational consistency, compliance, and control becomes increasingly difficult.
Agentic AI requires scalable, AI-ready infrastructure capable of supporting high-performance inference, distributed data access, Kubernetes orchestration, GPU acceleration, and secure operations across hybrid environments. Enterprises also need unified management, governance, and operational automation to consistently run AI across datacenters, public clouds, and edge locations.
Nutanix delivers an open AI ecosystem that gives organizations the flexibility to integrate leading AI models, infrastructure, frameworks, and cloud environments without operational lock-in. This open approach ensures enterprises can adapt as AI technologies evolve, allowing them to run workloads across models and infrastructure without dependence on a single vendor or architecture.
Nutanix provides a unified operating platform for agentic AI that helps organizations build, deploy, govern, and scale autonomous AI systems consistently across distributed environments. Nutanix simplifies AI infrastructure operations, supports GPU-enabled workloads, and enables centralized governance, security, compliance, and operational automation for agentic AI at scale.
Nutanix provides a consistent operating model across datacenters, public clouds, and edge environments. AI workloads can be deployed and moved as needed, enabling hybrid inference architectures and portable AI operations.
Nutanix centralizes access control across models, data, and enterprise systems. With role-based policies and governed access, organizations can control how AI agents and applications interact with internal tools and data.
The full story
This article is one source in a clustered incident — the cluster page carries the summary, timeline and every other outlet covering it.
