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Legacy storage is stifling AI Innovation. Set it free.

Legacy, high-performance storage was designed for predictable HPC workloads and optimized for performance scaling on parallel file systems. But AI has changed the game with modern, multimodal AI workloads—processing text, images, video, and more—concurrently across tens of thousands of high-powered GPUs.

Legacy storage is stifling AI Innovation. Set it free.

Legacy, high-performance storage was designed for predictable HPC workloads and optimized for performance scaling on parallel file systems. But AI has changed the game with modern, multimodal AI workloads—processing text, images, video, and more—concurrently across tens of thousands of high-powered GPUs.

Legacy storage is stifling AI Innovation. Set it free.

Legacy, high-performance storage was designed for predictable HPC workloads and optimized for performance scaling on parallel file systems. But AI has changed the game with modern, multimodal AI workloads—processing text, images, video, and more—concurrently across tens of thousands of high-powered GPUs.

Legacy storage is stifling AI Innovation. Set it free.

Legacy, high-performance storage was designed for predictable HPC workloads and optimized for performance scaling on parallel file systems. But AI has changed the game with modern, multimodal AI workloads—processing text, images, video, and more—concurrently across tens of thousands of high-powered GPUs.
Metadata overload hinders performance

Existing systems can’t keep up with metadata bottlenecks, causing inefficiencies and costly delays.

AI pipelines stall

Traditional storage lacks parallelism, requiring ongoing optimizations to feed massive GPU clusters at full speed.

Scaling is a nightmare

AI and HPC infrastructure needs fluid, seamless growth of data and metadata, but legacy storage systems are inherently complex and not designed for this level of flexibility.

It’s time for a data storage platform built to accelerate AI and HPC innovation.

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Legacy storage is stifling AI Innovation. Set it free.

Legacy, high-performance storage was designed for predictable HPC workloads and optimized for performance scaling on parallel file systems. But AI has changed the game with modern, multimodal AI workloads—processing text, images, video, and more—concurrently across tens of thousands of high-powered GPUs.
Metadata overload hinders performance

Existing systems can’t keep up with metadata bottlenecks, causing inefficiencies and costly delays.

AI pipelines stall

Traditional storage lacks parallelism, requiring ongoing optimizations to feed massive GPU clusters at full speed.

Scaling is a nightmare

AI and HPC infrastructure needs fluid, seamless growth of data and metadata, but legacy storage systems are inherently complex and not designed for this level of flexibility.

It’s time for a data storage platform built to accelerate AI and HPC innovation.

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