{"slug": "nutanix-adds-more-rooms-to-its-agentic-ai-building", "title": "Nutanix adds more rooms to its agentic AI building", "summary": "Nutanix announced the general availability of Nutanix Enterprise AI (NAI) 2.8 and the upcoming general availability of Nutanix Kubernetes Platform (NKP) 2.19, enhancing its Nutanix Cloud Platform for production agentic AI with centralized control, MCP gateway, and advanced inference capabilities. The update includes Parameter-Efficient Fine-Tuning with LoRA for models under 8B parameters, scalable multi-GPU serving via tensor parallelism, and speculative decoding that accelerates token generation by up to 2.5x. Thomas Cornely, Nutanix EVP of Product Management, emphasized that the dual-native architecture lets customers bring AI to existing applications without rebuilding systems or creating new silos.", "body_md": "HCI\n\n# Nutanix adds more rooms to its agentic AI building\n\n[Nutanix ](https://www.blocksandfiles.com/file/2026/07/28/nutanix-gets-dell-powerstore-support/5279629)announced the general availability of Nutanix Enterprise AI (NAI) 2.8, and the upcoming general availability of Nutanix Kubernetes Platform (NKP) 2.19.\n\nIt said its core Nutanix Cloud Platform (NCP) offering is being enhanced and expanded for production agentic AI with its dual-native, side-by-side, container and virtual machine architecture. NAI 2.8 provides centralized control for AI inference and agentic AI, including Nutanix Agent Gateway, with its Model Context Protocol (MCP) gateway for governing how agents connect with apps and data via MCP. Nutanix Private Inference provides enhanced capabilities for high-performance fine tuning and inference, along with improved security and governance. NKP 2.19 is expected to provide streamlined container management for bare metal and virtualized environments, with a built-in AI catalog designed for building and running agentic AI applications.\n\nThomas Cornely, Nutanix EVP, Product Management, said: “Enterprise AI should not require customers to rebuild the systems that already run their business. With our dual-native architecture, customers can bring AI to their existing applications and data while running each workload on the infrastructure best suited to it, with consistent operations and governance across VMs, containers and AI. This gives organizations a practical path to production without creating new silos or limiting future choice.”\n\nNutanix has been on a multi-month roll out of agentic AI support features, wanting its customers to have a smooth agentic AI adoption process. It added an open-source [MCP server](https://www.blocksandfiles.com/hci/2026/08/10/nutanix-adding-ai-agent-access-bridge-to-its-cloud-platform/5285493) to its Cloud Platform software earlier this month, so that AI agents can access it and use its resources. Its Agent Gateway was generally available as a control point to manage AI agent activity, access policies, and token consumption across agentic AI deployments in July.\n\nBack in April the [Nutanix Agentic AI](https://www.blocksandfiles.com/ai-ml/2026/03/18/storage-vendors-orbit-the-nvidia-sun-at-gtc/5209546) offering, announced at Nvidia's GTC event in March, integrated with Nvidia AI Enterprise at the Agent Builder layer and enabled customers to build, run, and protect agentic AI applications with a suite of infrastructure orchestration and security software. Now here are more bricks in its agentic AI wall.\n\nNutanix makes the point that many enterprises face a roadblock when deploying AI, because AI is accelerating the shift to containers, while legacy applications and data remain spread across both virtualized and containerized environments. This split can force enterprises to add infrastructure silos, move data or rearchitect existing workloads to support AI alongside the applications and data they already run. If they use Nutanix systems then no re-architecting is needed.\n\nNAI and NKP are designed to enable organizations to securely run, manage, and govern AI, containerized applications and virtualized workloads through a consistent control plane. Nutanix says it has new advanced inference and tuning capabilities;\n\nParameter-Efficient Fine-Tuning which supports Low-Rank Adaptation (LoRA) fine-tuning for smaller models (<8B parameters), helping organizations to cost-effectively customize open LLMs on private domain data using single-GPU compute while seamlessly deploying adapters straight to serving pipelines,\n\nScalable multi-GPU serving which enables high-throughput multiGPU inference via tensor parallelism, delivering fast, distributed serving across enterprise hybrid cloud environments,\n\nSpeculative decoding which accelerates LLM inference token generation by up to 2.5x using lightweight draft models, cutting output latency without sacrificing model accuracy.\n\nNAI’s APIs, featuring fine-grained Identity and Access Management (IAM), custom roles and seamless model sharing, enforces least-privilege security, helping ensure agents operate securely and restricting access to only authorized roles, as well as support for air-gapped Nvidia NIM microservices deployment.\n\nNPK’s upcoming release will provide an AI-optimized platform for building and running agentic applications at scale, including the following features:\n\n**NKP Metal:** Built to bring HCI-grade simplicity to bare-metal Kubernetes, with automated OS, firmware, container deployment, and persistent, enterprise-grade storage natively, eliminating the complexity of patchwork platforms.**NKP Full Stack:** While NKP Metal is intended to bring simplicity to bare-metal deployments, NKP on AHV combined with Nutanix Flow, is designed to deliver stronger network-level sandboxing for AI agents, helping provide isolation to mitigate the risk of rogue attacks and lateral movement.**AI Applications Catalog:** Offers a one-click deployment path for curated, validated AI/ML software (Kubeflow, Milvus, Slurm) to help bypass manual integration challenges.**Hardware and Compliance:** Planned expansion of ecosystem support with validated GPU integrations, alongside dynamic resource allocation for AI workloads.\n\nA new Powered by Nutanix: Verified Services program for partners should enable them to capitalize on VM-to-container industry shifts, and AI deployments, by building validated, high-margin services practices that span the customer lifecycle. Nutanix’ generally available Service Provider (SP) Central provides an adaptable multi-tenant cloud foundation, giving service providers facilities to grow infrastructure, platform, cloud-native, and AI services on their own terms.\n\nNAI 2.8 and SP Central are generally available now. NKP 2.19 will be available soon.", "url": "https://wpnews.pro/news/nutanix-adds-more-rooms-to-its-agentic-ai-building", "canonical_source": "https://www.blocksandfiles.com/hci/2026/08/26/nutanix-adds-more-rooms-to-its-agentic-ai-building/5292580", "published_at": "2026-08-26 13:21:28+00:00", "updated_at": "2026-08-26 13:45:02.900959+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-infrastructure", "ai-products", "ai-agents", "generative-ai"], "entities": ["Nutanix", "Nutanix Enterprise AI 2.8", "Nutanix Kubernetes Platform 2.19", "Nutanix Cloud Platform", "Nutanix Agent Gateway", "Model Context Protocol", "Nvidia", "Thomas Cornely"], "alternates": {"html": "https://wpnews.pro/news/nutanix-adds-more-rooms-to-its-agentic-ai-building", "markdown": "https://wpnews.pro/news/nutanix-adds-more-rooms-to-its-agentic-ai-building.md", "text": "https://wpnews.pro/news/nutanix-adds-more-rooms-to-its-agentic-ai-building.txt", "jsonld": "https://wpnews.pro/news/nutanix-adds-more-rooms-to-its-agentic-ai-building.jsonld"}}