Hammerspace helped a leading AI model developer overcome storage bottlenecks by enabling efficient use of thousands of GPUs' local NVMe storage, which was previously unused and costly. By integrating this local storage into a unified global data environment, Hammerspace provided scalable, high-performance storage without additional budget. This solution accelerated data access and management, allowing the company to meet aggressive time-to-market deadlines and support large-scale frontier language model training effectively, boosting overall compute resource utilization and productivity.

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