
AI storage that scales with demand, moves with your workloads, and fits the cloud environments you've already built.
PROVIDERS
CHALLENGES

Data bottlenecks limit usable compute. Add instances without adding storage performance, and more compute won't produce more work.

Cloud infrastructure costs the same whether it's doing useful work or waiting on data.

Starting compute is fast. Moving datasets isn't. So jobs run where data sits, not always where the best compute is available.
BENEFITS
Turn more of the compute, storage, and GPU capacity you already pay for into useful work.
Keep accelerated compute productive so more of what you spend on cloud infrastructure goes toward useful results.
Feed inference fleets with high-performance storage that keeps data bottlenecks from limiting users, throughput, and token generation.
Scale storage performance with compute so adding cloud resources increases throughput instead of dividing existing performance.
Put workloads where the right compute is available across regions, clouds, or on premises. Remote data becomes usable as it moves.
See what cloud compute can deliver when storage performance keeps pace.
0x
more concurrent users
Benchmark using NeuralMesh on OCI GPU infrastructure against a DRAM-only baseline.
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More Input Tokens
Measured with WEKA Augmented Memory Grid™ on AWS P6 instances with B200 GPUs and the same GPU footprint.
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GPU Utilization
Achieved by Stability AI running large-scale AI model training on AWS.
FEATURES
NeuralMesh adds and removes resources as demand changes, so storage performance and capacity scale with your cloud.

Eliminate pipeline latency, maximize GPU utilization, and move data fluidly across your cloud environment with NeuralMesh.
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