NVIDIA Run:ai B2B Case Studies & Customer Successes

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NVIDIA Run:ai accelerates AI and machine learning operations by addressing key infrastructure challenges through dynamic resource allocation, comprehensive AI life-cycle support, and strategic resource management. By pooling resources across environments and utilizing advanced orchestration, NVIDIA Run:ai significantly enhances GPU efficiency and workload capacity. With support for public clouds, private clouds, hybrid environments, or on-premises data centers, NVIDIA Run:ai provides unparalleled flexibility and adaptability.

Case Studies

Showing 7 NVIDIA Run:ai Customer Success Stories

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King’s College London achieves 31× faster experiments and 2.1× higher GPU utilization with NVIDIA Run:ai

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Leading Global Bank achieves 10x more data scientists per GPU and faster time-to-market with NVIDIA Run:ai

Multinational facial-recognition leader achieves 73% GPU utilization and 2X faster training with NVIDIA Run:ai

NVIDIA achieves 4.7× inference throughput and ~95% GPU utilization with NVIDIA Run:ai

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Salk Institute achieves 'unlimited' pooled GPU compute and flexible, fair access with NVIDIA Run:ai

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Wayve achieves >80% GPU utilization with NVIDIA Run:ai

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Zebra Technologies achieves seamless hybrid on-prem and cloud model training with NVIDIA Run:ai

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