# Vdura's storage platform update targets neoclouds with multi-tenancy and tiering > Source: > Published: 2026-09-30 14:44:16+00:00 Software-defined storage vendor Vdura has unveiled the latest version of its flagship platform with additions aimed at capturing demand from GPU clouds and so-called AI factories. Data Platform Version 12, now generally available, can scale across anything from eight to 100,000 GPUs on a single software stack. The vendor touted improvements including up to 20-times faster metadata, context-aware tiering so data moves between flash and hard drives based on how it's used, and more than 60% lower total cost of ownership versus competing architectures at the same feed rate. Available now for V5000-class data storage arrays, the platform can be deployed in a multi-tenancy configuration, so a single storage pool is split across isolated tenant environments, each of which comes with their own performance guarantees, encryption keys and virtual local area networks (VLANs) – with Vdura touting it for firms renting GPU access, like neoclouds. The crux of Vdura’s V12 update then is ensuring better performance per watt and lower cost, so GPUs are kept busy while using less power and rack space. “Neocloud and AI factory operators told us exactly what they need from storage: keep the GPUs fed, isolate the tenants, automate everything, expand capacity for cold data without a second system, and move that data back to flash the moment it warms up for extended context," Vdura CEO Ken Claffey said. “V12 is that list, shipped. It is the same mixed-fleet, software-defined model the hyperscalers run inside their own clouds, delivered on Supermicro systems our customers already buy. Every watt and every rack unit we give back is another GPU the operator can put into service.” Central to V12 is HYDRA, its High-performance, Yield-optimized, Distributed, Resilient Architecture which the company says it has extended with the multi-tenant, API-driven capabilities GPU clouds require. For example, the vendor claims a single platform of roughly 20 petabytes usable can span a 35-fold performance range, from a capacity-optimized mixed fleet with 2% flash drawing 18 kilowatts to an all-flash configuration delivering 1,000 megabytes per second per terabyte. V12 also features what Vdura billed as “RDMA data paths” (remote direct memory access), which enable direct transfers between the GPU and storage, cutting out the CPU. The vendor’s DirectFlow parallel client, which runs on the GPU server eliminates the need for an extra hop to the processor, a process Vdura claims takes roughly 191 megabytes of dynamic random-access memory and no CPU cores. “Every kilowatt spent on storage is a kilowatt not spent on compute. V12 was engineered for that operating model: keep every GPU fed, keep every tenant isolated, keep every cluster online, and do it on hardware operators already standardize on,” the vendor’s announcement reads.