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github.com/mpwusr
Any of them. Our AI OS treats compute as a heterogeneous, multi-substrate fabric — NVIDIA (L4, A100, H100), AMD, edge accelerators, and the sub-$350 GPUs targeted by TALON-EDGE — and routes work to whatever hardware delivers the best utilization and cost.
TALON-EDGE turns a drone swarm into a distributed compute fabric. Each drone advertises its compute capability, work is routed to the best available GPU in the mesh, and if a drone is lost the swarm automatically redistributes its load — no manual reconfiguration.
We baseline your current GPU spend and utilization, surface idle and stranded capacity, and continuously optimize placement across substrates. The goal is measured outcomes — higher utilization and lower effective cost per unit of work.
The AI OS is a substrate-agnostic control plane that schedules AI workloads across heterogeneous GPUs, cloud, on-prem, and edge as a single fabric. It abstracts the hardware so the same workload runs wherever it is most efficient at any moment.
From proof-of-concept to production GPU clusters. Let's build your AI infrastructure together.
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