Music AI needed faster access to powerful compute without unpredictable costs to scale their ambitious AI audio product portfolio. Training advanced models for stem separation, voice modeling, and real-time transformation required consistent GPU access and distributed compute across large datasets.

Music AI implemented Vultr Bare Metal GPU servers with 8x NVIDIA H100 GPUs, enabling distributed training on PyTorch and Ray while maintaining predictable costs and avoiding vendor lock-in across their multi-cloud strategy.