WoolyAI

We are building the world’s first hardware-agnostic hypervisor for machine learning GPU clusters, enabling unmodified PyTorch and inference workloads to run seamlessly across NVIDIA and AMD GPUs. This hypervisor abstracts away hardware differences, allowing ML teams to avoid code rewrites, improve deployment speed, and achieve greater infrastructure flexibility. With WoolyAI, GPU resources—including cores and memory—can be dynamically shared across models based on demand and priority, boosting utilization and enabling concurrent, isolated model execution. The platform consists of GPU-agnostic portable Wooly client containers, a central controller for orchestrating across heterogeneous GPU clusters, and an execution server. This architecture supports live workload migration, simplifies ML operations, and ensures reliable, scalable multi-model deployment. Contact us if you want to try out our Beta.