Nutanix has announced the general availability of the latest version of the Nutanix Enterprise AI (NAI) solution, adding deeper integration with NVIDIA AI Enterprise, including NVIDIA NIM microservices and the NVIDIA NeMo framework, to speed the deployment of Agentic AI applications in the enterprise.
NAI is designed to accelerate the adoption of generative AI in the enterprise by simplifying how customers build, run, and securely manage models and inferencing services at the edge, in the data center, and in public clouds on any Cloud Native Computing Foundation (CNCF)-certified Kubernetes environment.
The latest NAI release extends a shared model service methodology that simplifies agentic workflows, helping to make deployment and day two operations simpler. It streamlines the resources and models required to deploy multiple applications across lines of business with a secure, common set of embedding, reranking, and guardrail functional models for agents. This builds on the NAI core, which includes a centralized LLM model repository that creates secure endpoints that make connecting generative AI applications and agents simple and private.
“Nutanix is helping customers keep up with the fast pace of innovation in the Gen AI market,” said Thomas Cornely, SVP of Product Management at Nutanix. “We’ve expanded Nutanix Enterprise AI to integrate new NVIDIA NIM and NeMo microservices so that enterprise customers can securely and efficiently build, run, and manage AI Agents anywhere.”
“Enterprises require sophisticated tools to simplify agentic AI development and deployment across their operations,” said Justin Boitano, Vice President of Enterprise AI Software Products at NVIDIA. “Integrating NVIDIA AI Enterprise software including NVIDIA NIM microservices and NVIDIA NeMo into Nutanix Enterprise AI provides a streamlined foundation for building and running powerful and secure AI agents.”
NAI for agentic applications can help customers:
- Deploy Agentic AI Applications with Shared LLM Endpoints – Customers can reuse existing deployed model endpoints as shared services for multiple applications. This re-use of model endpoints helps reduce usage of critical infrastructure components, including GPUs, CPUs, memory, file and object storage, and Kubernetes clusters.
- Leverage a Wide Array of LLM Endpoints – NAI enables a range of agentic model services, including NVIDIA Llama Nemotron open reasoning models, NVIDIA NeMo Retriever and NeMo Guardrails. NAI users can leverage NVIDIA AI Blueprints, which are pre-defined, customizable workflows, to jumpstart the development of their own AI applications that leverage NVIDIA models and AI microservices. In addition, NAI enables function calling for the configuration and consumption of external data sources to help AI agentic applications deliver more accurate and detailed results.
- Support Generative AI Safety – This new NAI release will help customers implement agentic applications in ways consistent with their organization’s policies using guardrail models. These models can filter initial user queries and LLM responses to prevent biased or harmful outputs and can also maintain topic control and jailbreak attempt detection. For example, NVIDIA NeMo Guardrails are LLMs that provide content filtering to filter out unwanted content and other sensitive topics. These can also be applied to code generation, providing improved reliability and consistency across models.
- Unlock Insights From Data with NVIDIA AI Data Platform – The Nutanix Cloud Platform solution builds on the NVIDIA AI Data Platform reference design and integrates the Nutanix Unified Storage and the Nutanix Database Service solutions for unstructured and structured data for AI. The Nutanix Cloud Infrastructure platform provides a private foundation for NVIDIA’s accelerated computing, networking, and AI software to turn data into actionable intelligence. As an NVIDIA-Certified Enterprise Storage solution, Nutanix Unified Storage meets rigorous performance and scalability standards, providing software-defined enterprise storage for enterprise AI workloads, through capabilities such as NVIDIA GPUDirect Storage.
NAI is designed to use additional Nutanix platform services while allowing flexible deployments on HCI, bare metal, and cloud IaaS. NAI customers can also leverage the Nutanix Kubernetes Platform solution for multicloud fleet management of containerized cloud native applications, and Nutanix Unified Storage (NUS) and Nutanix Database Service (NDB) as discrete data services, offering a complete platform for agentic AI applications.
“Customers can realize the full potential of generative AI without sacrificing control, which is especially important as businesses expand into agentic capabilities,” said Scott Sinclair, Practice Director, ESG. “This expanded partnership with NVIDIA provides organizations an optimized solution for agentic AI minimizing the risk of managing complex workflows while also safeguarding deployment through secure endpoint creation for APIs. AI initiatives are employed to deliver strategic advantages, but those advantages can’t happen without optimized infrastructure control and security.”
