Nutanix, a leader in cloud infrastructure solutions, has taken a significant step forward in supporting the deployment of generative AI (GenAI) applications with the launch of Nutanix Enterprise AI (NAI), a new cloud-native offering that extends the company’s AI platform. This platform can now be deployed on any Kubernetes-based environment, spanning edge locations, core data centers, and public cloud services like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), and Google Kubernetes Engine (GKE). According to Nutanix, this flexibility allows organizations to deploy AI workloads with enhanced efficiency and security, and importantly, to choose the location that best fits their needs while maintaining control over their data. As AI continues to evolve rapidly, Nutanix aims to address the complexities of managing AI models, data, and workloads across diverse infrastructures, all while optimizing the return on investment (ROI) for enterprises.
Nutanix’s Enterprise AI platform builds on the core principles of hybrid and multicloud IT environments, which are increasingly critical in the context of AI. The report highlights that 94% of enterprises are using a hybrid IT approach to balance the performance of cloud workloads with the security and control offered by on-premises infrastructures. This adoption is driven by the need to maintain data privacy, minimize latency, and optimize costs, all of which are key to implementing AI at scale. With the addition of Nutanix Enterprise AI, businesses can now simplify the process of deploying, running, and scaling large language models (LLMs) and other GenAI applications, significantly reducing the deployment time—from weeks to minutes.
Simplified AI Workflows with Multicloud and Hybrid Deployment Support
The nature of generative AI workloads is inherently hybrid, with different stages of the AI lifecycle often happening across different environments. For example, AI models are typically developed and fine-tuned using private data on-premises or in controlled environments, while inference (the process of using the trained model to make predictions or generate outputs) is often deployed closer to where the data resides—at the edge, on-premises, or in the cloud. This distributed, hybrid workflow can create challenges for businesses, particularly around complexity, data privacy, security, and cost.
Nutanix Enterprise AI is designed to resolve these challenges by offering a consistent multicloud operating model, enabling organizations to seamlessly run and scale AI workloads. The platform integrates with NVIDIA NIM (NVIDIA Inference Microservices), which optimizes the performance of foundation models, making it easier for organizations to deploy, manage, and scale large language models quickly. Nutanix reports that customers using this platform can deploy GenAI applications in less than one hour, a significant reduction compared to traditional methods that could take days or even weeks. In fact, 70% of surveyed organizations said they experienced substantial improvements in the time-to-deployment of their AI workloads after switching to Nutanix’s AI platform.
With a focus on multicloud flexibility, Nutanix Enterprise AI can be deployed across various public clouds like AWS, Azure, and Google Cloud, while also integrating smoothly with on-premises deployments. By allowing businesses to choose the best infrastructure for their workloads, Nutanix ensures that enterprises have the scalability and security they need to support the most demanding AI applications. The consistent deployment model across on-premises and public cloud environments means that IT teams no longer need to worry about managing multiple disparate systems, improving both operational efficiency and security compliance.
Optimized Performance and Predictable Pricing for AI Workloads
One of the standout features of Nutanix Enterprise AI is its ability to provide high-performance AI workloads with predictable pricing. Many organizations that adopt generative AI struggle with the unpredictability of costs, especially when pricing is based on token-based or usage-based models that are difficult to forecast. This lack of predictability can be a significant barrier for enterprises that are looking to scale AI applications, as costs can escalate rapidly without clear visibility into usage patterns.
Nutanix Enterprise AI addresses this concern with a transparent and predictable pricing model based on infrastructure resources used for AI workloads. This predictable cost structure ensures that businesses can confidently scale their AI initiatives while managing operational expenses effectively. In a market where cloud services often offer opaque pricing structures, this approach is a game-changer. According to Nutanix, organizations using this pricing model reported a 25% reduction in unexpected cloud spend, helping them maximize their ROI while avoiding unforeseen costs.
Moreover, Nutanix Enterprise AI’s integration with NVIDIA’s AI Enterprise software platform ensures that organizations benefit from optimized performance for LLMs and other AI models. The NVIDIA NIM microservices further enhance the platform’s capabilities by providing secure, reliable deployment options for high-performance AI inferencing. Nutanix has confirmed that 98% of organizations that used NVIDIA NIM alongside Nutanix Enterprise AI experienced a 20% improvement in model performance compared to other infrastructure configurations. This level of optimization is critical for organizations deploying mission-critical AI applications that require consistently high performance and low latency.
Simplifying AI Deployment with User-Friendly Interfaces and AI Admin Tools
As the demand for generative AI grows, businesses are increasingly faced with the challenge of building AI-ready infrastructure. Many organizations, particularly those without deep expertise in AI, struggle with creating the necessary platform to support the specific requirements of AI workloads, including scalability, performance, and security. Nutanix Enterprise AI offers a streamlined approach to deploying and managing AI models, making it easier for IT teams to adapt to the complexities of AI infrastructure.
The platform features a simple UI-driven workflow that allows users to quickly deploy, test, and scale large language model (LLM) inference endpoints. According to Nutanix, 85% of organizations that deployed Nutanix Enterprise AI reported that they were able to launch their AI workloads without requiring specialized AI knowledge, thanks to the platform’s intuitive interface. The integration with Hugging Face, an open-source AI community that provides pre-trained models, further simplifies the process for users, allowing them to leverage existing models for their applications. This level of simplicity is crucial for IT admins who need to manage AI workloads without becoming AI experts themselves.
Additionally, Nutanix Enterprise AI helps mitigate the AI skill shortage that many organizations face. By providing an easy-to-use interface and built-in features for managing AI infrastructure, Nutanix enables IT administrators to take on roles typically reserved for AI specialists, accelerating AI development across the organization. As a result, businesses can deploy AI solutions more quickly and with fewer personnel, cutting down on the time it takes to see a return on investment.
Ensuring Security and Compliance for AI Workloads
Security and data privacy are top concerns for organizations deploying AI applications, particularly when working with sensitive or proprietary data. Nutanix Enterprise AI is designed with these concerns in mind, providing robust security features to ensure that AI workloads are deployed and managed securely. The platform allows customers to run their AI models and store their data in environments that they control, whether on-premises, at the edge, or in the public cloud. This flexibility ensures that sensitive data never leaves the organization’s controlled infrastructure, reducing the risk of data breaches or compliance violations.
The platform also includes an intuitive dashboard for observability and troubleshooting, which provides IT teams with detailed insights into the performance and utilization of AI resources. This feature allows administrators to quickly address potential issues before they affect AI model performance, ensuring that applications run smoothly and securely. Additionally, role-based access controls (RBAC) are built into Nutanix Enterprise AI, enabling businesses to maintain fine-grained control over who can access AI models and data, further enhancing security and compliance.
For organizations with stringent security requirements, Nutanix Enterprise AI supports deployment in air-gapped or dark-site environments, ensuring that even the most sensitive workloads can be managed securely without exposure to external networks. This level of security is critical for industries such as finance, healthcare, and government, where data privacy and regulatory compliance are non-negotiable.
Conclusion
Nutanix’s Enterprise AI platform represents a major advancement in the way businesses can deploy, scale, and manage generative AI applications. By offering a consistent, multicloud approach that integrates seamlessly with both on-premises and public cloud environments, Nutanix addresses the most pressing challenges organizations face in AI adoption. The platform’s integration with NVIDIA NIM microservices and Hugging Face foundation models further enhances its capabilities, ensuring optimized performance for AI workloads.
With simplified deployment processes, transparent pricing, and robust security features, Nutanix Enterprise AI is helping organizations accelerate their AI initiatives, improve ROI, and reduce operational complexity. As the demand for AI solutions continues to grow, Nutanix’s approach is poised to empower businesses across industries to harness the full potential of generative AI while maintaining the control, performance, and security they need for mission-critical applications.
By delivering a flexible, secure, and cost-effective AI infrastructure platform, Nutanix is positioning itself as a leader in the next generation of AI infrastructure, helping organizations navigate the challenges of an increasingly AI-driven world.
