Own the metal your students learn on.
A right-sized GPU pod on a spine-leaf, lossless-Ethernet fabric. Runs your AI workloads and IS the teaching platform.
What it is
The problem it removes.
A right-sized GPU pod sits on a spine-leaf, lossless-Ethernet (RoCE) fabric built for GPU training traffic. VMs and Kubernetes carve isolated virtual labs, one per class. A final-year student SSH-ing into a real GPU cluster is a graduate employers fight over — and the same pod runs your research and displaces the cloud bill.
How it works
Engineered, not improvised.
Spine-leaf, lossless-Ethernet (RoCE) fabric engineered for GPU training traffic
VMs and Kubernetes carve isolated virtual labs, one per class
A right-sized GPU pod scaled to your teaching and research load
Quota-governed, monitored compute access per student and cohort
The benefit
What your institution gets back.
Converts escalating cloud rental into an owned, depreciating, revenue-generating asset
No latency, no egress fees, no data leaving campus
Addresses the ~53% AI talent gap — niche AI-infra graduates command up to 1.7x pay
The rest of the suite
Each stands alone. Together they compound.
Own the metal your students learn on.
Every transformation starts with Phase 0 — a free discovery workshop, RF site survey and silent-tax audit. No commitment beyond the conversation.