Wand AI today announced the addition of StorONE, the leader in Real-Time Tiering architecture, to its Sovereign AI offering, giving sovereign programs a new option for raising the utilization of their storage, as the Wand backend already does for their compute. By incorporating StorONE’s Real-Time Tiering into the Wand ecosystem, programs that elect it can serve the same AI workloads on a fraction of the flash they would otherwise have to buy without losing performance or immediate access to any of their data.
A sovereign AI program has two scarce assets, GPUs and storage. Both must run at high utilization for national AI to be affordable at scale.
National AI infrastructure is judged on cost per outcome, and cost per outcome is a utilization problem. Wand’s sovereign backend already attacks the compute half: by letting every data owner run on shared capacity rather than a dedicated carveout, the architecture is designed to raise utilization of national compute from roughly 25% to more than 80%. Storage is the other half of the bill, and it is still bought the old way.
However, AI storage is provisioned for its peak, so nearly all of it is flash, even though, at any given moment, most of the data sitting on it is inactive. The expensive tier runs at low utilization by construction. Capacity compounds the problem. Bought per workload and per protocol, it strands in silos that cannot be lent to the workload that actually needs it. A nation ends up buying its most expensive media to hold its coldest data, and buying it again for the next workload.
The existing storage market does not resolve this. Data reduction returns roughly 30% to 40% capacity savings while consuming 80% to 85 % of CPU and memory overhead — paying for storage efficiency with the compute the AI stack was built to use. Archive tiers lower the bill by putting cold data behind a restore step, which is the one thing a retrieval workload cannot tolerate. And proprietary arrays tie capacity to hardware only one vendor can supply, at a moment when sovereign programs need to buy the drives that are actually available to them.
The addition of StorONE closes that gap. The company’s Real-Time Tiering writes all data to flash at full performance, then continuously identifies inactive blocks and moves only those to high-capacity media inside the same volume — no policies, no bolt-on tools, no restore step, and every block immediately accessible. StorONE reports approximately 90% average flash savings at roughly 10% cost-performance and overhead impact, against the 30% to 40% that legacy data reduction returns for 80%to 85% overhead.
Because the ONE-Volume Architecture separates storage services from hardware, any server, any drive, across block, file, and object, capacity is pooled across workloads instead of stranded in per-workload arrays, and a nation can build that pool from whatever media it can source. StorONE is elective rather than required: the Wand backend runs on a program’s existing storage where those economics already work, and StorONE is brought in where flash cost, footprint, or power is the binding constraint.
“Nations are sizing AI programs around GPU utilization and then quietly losing the same money one layer down, on flash that is mostly holding cold data,” said Gal Naor, Founder and CEO of StorONE. “Real-Time Tiering moves only the inactive blocks to high-capacity media inside the same volume, so everything stays immediately accessible. One of our enterprise customers went from nine cabinets to two, resulting in an 80% smaller footprint and 78% drop in power usage. At national scale, that is capacity, megawatts, and capital returned to the AI program.”
“Sovereign AI is an economics question before it is a technology question, and the answer is utilization on both sides of the stack. We are pleased to welcome StorONE into Wand’s sovereign technology ecosystem, adding a storage efficiency capability that ministries, institutions, and agencies can draw on where flash economics are the constraint, serving the same workloads on far less flash, and spending the difference on the AI labor itself,” said Cristian Felix, Chief AI Architect of Wand AI.
Utilization is raised on two axes. Flash utilization. Everything is written to flash at full performance; real-time algorithms continuously separate active from inactive data and relocate only the required blocks to high-capacity media within the same volume. The hot working set keeps flash economics on the data that earns them, and the cold majority stops occupying the most expensive tier while remaining directly addressable, with no external system, copy, or recall in the path. Capacity utilization. One platform serves all protocols and all media on standard hardware, with each volume carrying its own performance, protection, and retention parameters. Capacity is drawn from a shared pool rather than committed to a dedicated array per workload, so a ministry’s unused terabytes are available to the ministry that needs them.
The effect compounds beyond the storage line item. Less flash for the same workload means fewer racks, less power, and less cooling in one enterprise deployment, a reduction from nine cabinets to two, with an 80% decrease in data center footprint and a 78% reduction in power consumption. In a national AI build, those are the constraints that determine how much GPU a program can actually stand up.
The capability is complementary to the inference privacy, confidential computing, and model robustness layers already in Wand’s sovereign ecosystem. Those raise the utilization and trustworthiness of national compute; StorONE raises the utilization of the storage underneath it. The capabilities are independent, each can be adopted on its own, and none is a prerequisite for another, but they move the same number: cost per outcome for every ministry and agency the sovereign backend serves.
Wand AI is building the sovereign infrastructure for AI labor. Wand’s operating system enables governments and enterprises to deploy, manage, govern and continuously evolve AI agents alongside humans as trusted members of the workforce, with identity, objectives, authority, security, governance and auditability built into the platform.
For nations, Wand provides a unified foundation through which ministries, public institutions, and critical national organizations can deploy AI labor while maintaining sovereign control over models, compute, data, policies and operations. Wand powers production-scale deployments with some of the world’s most consequential institutions, including leading banks, asset management firms, hedge funds, consulting firms, and system integrators. Wand exists to power the biggest transition in human history: infinite labor—so that everything humanity can imagine, we can finally build.
Founded in 2023 and headquartered in Palo Alto, California, with offices in Palo Alto, New York and Abu Dhabi, Wand is backed by world-class investors, leaders, and a tier-one research team. Learn more at wand.ai.
StorONE delivers up to 9x more value from flash through a single, hardware-agnostic enterprise storage software platform, validated by leading storage hardware manufacturers. Its patented Real-Time Tiering (RTT) manages data across flash and HDD within the same active production volume, automatically and transparently placing data on the appropriate media while keeping all data online and immediately accessible.
The same enterprise storage services, including snapshots, replication, data protection, and encryption are available across all tiers. StorONE supports block, file, and object protocols and works with leading servers and drive technologies, giving customers the freedom to choose hardware based on price and availability and expand without hardware compatibility constraints or vendor lock-in.
For more information, visit StorONE or follow StorONE on LinkedIn.