This solution brief presents KAI Torch, a platform that lets AI rack manufacturers, OEMs, ODMs, and hyperscalers validate infrastructure against hundreds of emulated training racks without building a full physical cluster. Running on Keysight APS-One hardware, it executes real PyTorch workloads, Chakra execution graphs, NCCL collectives, and models such as ResNet and Llama. Teams can test compute, networking, storage, synchronization, power, thermal behavior, and congestion under realistic distributed conditions. Custom dashboards track GPU efficiency, network use, and power consumption, helping uncover interoperability and performance issues before deployment while reducing hardware costs, qualification time, and production risk.

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