Capital idea, Nutanix ups case for AI workloads with Nvidia cert
Some companies like to add AI (or .ai) to their core organisational designation and moniker these days… it’s cute enough, but one imagines it’ll be superseded by the next big thing once agentic intelligence has conquered the world.
Other firms use camelCase to try and stand out… while others still are fond of trying to capitalise their brand name in full.
Known for its predeliction for capitalisation almost as much as its work with Graphics Processing Units (GPUs), Nvidia offers its Nvidia-Certified label as a way of validating enterprise technologies to ensure they optimally run AI, data science and accelerated computing workloads with maximum performance.
Now proudly showing off its new status in this regard is hybrid multicloud computing company Nutanix, which this week announced the Nutanix Unified Storage (NUS) solution is Nvidia-Certified at the enterprise level.
Nutanix is also advancing AI-native storage with planned support for Nvidia Vera BlueField-4 STX (high-speed storage processing and in-silicon threat detection to protect context memory for agentic AI workloads), reinforcing its focus on faster data access, greater storage efficiency and simpler AI operations.
Building AI factories
As enterprises and cloud providers race to build AI factories to support production AI workloads, Nutanix says they require infrastructure that can keep data moving, maximise GPU utilisation and reduce deployment risk.
“Success depends not only on access to powerful GPUs but on the ability to feed those systems with data efficiently and reliably. Fragmented infrastructure, siloed data, and inconsistent performance can slow deployments, limit GPU efficiency, and make AI harder to scale reliably,” said the company, in a press statement.
With this certification, Nutanix is providing enterprises and cloud providers with a validated configuration to support enterprise deployment of AI infrastructure. The certification helps ensure NUS is validated for full-stack interoperability with Nvidia AI infrastructure, helping to reduce I/O bottlenecks and integration risk.
Data-hungry demands of AI
By enabling linear scalability for the data-hungry demands of AI workloads, it helps ensure an organisation’s most valuable assets, its GPUs and data, are working at maximum efficiency in production environments.
“To build and run AI factories successfully, enterprises must move past fragmented infrastructure and data silos that limit GPU infrastructure efficiency,” said Thomas Cornely, executive vice president, product management, Nutanix. “This Nvidia certification validates that Nutanix Unified Storage delivers the full-stack interoperability, linear scalability, and reliable data velocity that modern AI workloads demand. By collaborating closely with Nvidia, we are giving customers a unified, high-performance foundation to scale their production AI operations with confidence.”
Built on a 10-node, all‑NVMe cluster, NUS uses enhanced parallel NFS (pNFS) and GPUDirect Storage over NFS with RDMA to establish a low-latency, high-throughput, and resilient data path directly between GPUs and storage, maximising utilisation while minimising downtime.
The result is a foundation for enterprise AI that helps customers move from targeted GPU deployments to larger production environments while keeping storage performance predictable as AI workloads expand.