Nutanix Expands AI Capabilities with New Enterprise AI Solution for Hybrid Multicloud
Nutanix expands AI infrastructure with Nutanix Enterprise AI, a scalable solution enabling secure, hybrid deployment of generative AI workloads across edge, on-premises, and public clouds.
Nutanix, a leader in hybrid multicloud computing, has announced an expansion of its AI infrastructure platform with a new cloud-native solution, Nutanix Enterprise AI (NAI). This can be deployed on any Kubernetes platform, at the edge, in core data centres, and on public cloud services like AWS EKS, Azure AKS, and Google GKE. The NAI solution provides a consistent hybrid multicloud operating model for accelerated AI workloads, enabling organisations to leverage their models and data in a secure location of their choice while improving return on investment (ROI). Utilising NVIDIA NIM for optimised performance of foundation models, Nutanix Enterprise AI helps organisations securely deploy, run, and scale inference endpoints for large language models (LLMs), supporting the deployment of generative AI (GenAI) applications in minutes rather than days or weeks.
Generative AI is an inherently hybrid workload, with new applications often built in the public cloud, fine-tuning of models using private data occurring on-premises, and inferencing deployed closest to the business logic, which could be at the edge, on-premises or in the public cloud. This distributed hybrid GenAI workflow can present challenges for organisations concerned about complexity, data privacy, security, and cost.
Nutanix Enterprise AI provides a consistent multicloud operating model and a simple way to securely deploy, scale and run LLMs with NVIDIA NIM optimised inference microservices as well as open foundation models from Hugging Face. This enables customers to stand up enterprise GenAI infrastructure with the resiliency, day 2 operations, and security they require for business-critical applications, on-premises or on AWS Elastic Kubernetes Service (EKS), Azure Managed Kubernetes Service (AKS), and Google Kubernetes Engine (GKE).
Additionally, Nutanix Enterprise AI delivers a transparent and predictable pricing model based on infrastructure resources, which is important for customers looking to maximize ROI from their GenAI investments. This is in contrast to hard-to-predict usage or token-based pricing.
Nutanix Enterprise AI is a component of Nutanix GPT-in-a-Box 2.0. GPT-in-a-Box also includes Nutanix Cloud Infrastructure, Nutanix Kubernetes Platform and Nutanix Unified Storage along with services to support customer configuration and sizing needs for on-premises training and inferencing. For customers looking to deploy in public cloud, Nutanix Enterprise AI can be deployed in any Kubernetes environment but is operationally consistent with on-premises deployments.
With Nutanix Enterprise AI, we’re helping our customers simply and securely run GenAI applications on-premises or in public clouds. Nutanix Enterprise AI can run on any Kubernetes platform and allows their AI applications to run in their secure location, with a predictable cost model.
– Thomas Cornely, SVP, Product Management, Nutanix
Nutanix Enterprise AI can be deployed with the NVIDIA full-stack AI platform and is validated with the NVIDIA AI Enterprise software platform, including NVIDIA NIM, a set of easy-to-use microservices designed for secure, reliable deployment of high-performance AI model inferencing. Nutanix-GPT-in-a-Box is also an NVIDIA-Certified System, also ensuring reliability of performance.
Generative AI workloads are inherently hybrid, with training, customisation, and inference occurring across public clouds, on-premises systems, and edge locations. Integrating NVIDIA NIM into Nutanix Enterprise AI provides a consistent multicloud model with secure APIs, enabling customers to deploy AI across diverse environments with the high performance and security needed for business-critical applications.
– Justin Boitano, Vice President of Enterprise AI, NVIDIA