The Data Acceleration Company

Stop paying for idle GPUs.

The Qumulo Cloud AI Accelerator presents your distributed enterprise data in real time to GPUs in any region or any cloud — with zero copies. Turn GPU hunting from a logistics gamble into a scheduling operation.

Request a demo See how GPU Liquidity works
0%
of accelerated compute sits idle waiting on data
0%
of AI workloads run in the public cloud
1EB
of customer data deployed for AI workloads
<0.05%
performance loss across 2,000 miles
The first 100 miles

The real bottleneck in AI isn't GPU scarcity. It's data gravity.

The industry obsesses over last-mile caching that makes GPUs efficient during token generation. It ignores the first 100 miles — getting petabyte-scale data to the GPUs at all. Before a single workload begins, data is copied, staged, and copied again.

The old way Weeks before a single GPU cycle
Copy to cloud → stage to NVMe → copy againdata staging & replication GPU computefinally

Up to 40% of GPU runtime burned loading data — paid-for compute, sitting idle.

With Qumulo Compute starts immediately
Connect<15 min GPU compute on live datazero copies, presented in real time

Data is presented in real time. No staging, no replication, no idle spend.

~5%

Typical enterprise GPU utilization under the old model. You pay for idle compute while hundreds of terabytes move into position — and every copy breaks consistency with the live dataset.

The Qumulo approach

GPU Liquidity, not data logistics.

Rather than moving massive datasets to wherever GPUs happen to be, Qumulo presents distributed data to GPUs in real time. Compute opens in a new region? Point your existing data at it — no replication, no staging delay.

On-premises Qumulo Core Edge & cloud Cloud Native Qumulo Cloud AI Accelerator + NeuralCache via Cloud Data Fabric — single namespace AWS Azure Google Cloud OCI
Live data presented in real time NeuralCache demand-driven prefetch Zero copies, no pre-staging
One fabric, three engines

What powers the Accelerator

Three layers turn distributed enterprise data into a single, real-time source for any GPU, wherever it runs.

High-performance storage

Cloud Native Qumulo

Extreme cloud performance that scales independently from capacity — no replicated storage islands, no brittle architectures.

Single global namespace

Cloud Data Fabric

A stretched filesystem that spans on-premises, edge, and every major cloud — presenting one consistent view of your data to any GPU, anywhere.

AI-driven prefetch

NeuralCache

Self-optimizing, demand-driven data positioning anticipates what the workload needs next — so analysis begins instantly, with no data-load phase.

Why it matters

Built to eliminate the GPU hunting tax

Eliminate the GPU hunting tax

Stop paying for idle compute while data moves into position.

  • No weeks-long data-staging delays
  • No repeated dataset replication
  • Run workloads wherever GPUs free up

AI data fabric for the hybrid enterprise

A unified fabric across on-premises, edge, and multi-cloud — fully cloud native on AWS, Azure, GCP, or OCI, with a global namespace across every endpoint.

Performance without tradeoffs

Extreme throughput with elastic scale for burst AI workloads — capacity and performance scale independently.

GPU hunting without replication

GPUs across regions and clouds access the same live dataset — no data-gravity constraints, lower egress and duplication costs.

Built for real enterprise AI

Production training and inference across healthcare, manufacturing, media, autonomy, and financial services — exabyte-scale, consistent everywhere.

Proof points

Extreme cloud performance, validated

Joint testing with multiple cloud AI/ML teams confirms cloud-scale throughput — and near-zero performance loss across thousands of miles.

0TB/s+
throughput on Cloud Native Qumulo
0M IOPS
on AWS, scaling elastically
<0.05%
performance loss region-to-region across 2,000 miles
<15min
to deploy an Accelerator in any cloud region
In production today

Real workloads, real outcomes

Hybrid AI pipelines

Use cloud AI without moving compliant data out of the data center

A leading financial institution wanted Microsoft AI Foundry but couldn't pull compliant data out of its data center. With Qumulo, it projects that data to a Cloud AI Accelerator in Azure — directly into AI Foundry — without ever copying or staging it outside its secure systems. The result: check-fraud detection, compliance validation, and customer-360 dashboards on live data.

0
copies of compliant data leave the secure perimeter
The difference

Qumulo vs. legacy AI storage

Capability
Qumulo Cloud AI Accelerator
Legacy AI storage
Data location
Accessed instantly across regions & clouds
Tied to a single location
Data movement
Demand-driven, zero-copy
Replication-heavy architecture
Scale
Elastic performance & capacity
Fixed infrastructure sizing
Namespace
Unified global namespace
Storage silos across environments
Designed for
Hybrid & multi-cloud AI
Single-environment focus
Fits your stack

Zero-copy into the AI platforms you already use

AI-as-a-Service platforms

Present live enterprise data to managed AI services — no exfiltration, no staging.

Orchestration frameworks

Works with the schedulers and pipelines your AI teams already run in production.

Kubernetes Slurm Ray SkyPilot Training & inference

Any Data. Any Location. Total Control.

See how the Qumulo Cloud AI Accelerator turns your distributed data into GPU liquidity — and stops the idle-GPU bill.

Request a demo Read the launch story