Engineering approach
We work across the whole server, not only the GPU.
Reliable AI infrastructure depends on component compatibility, firmware, Linux, drivers, storage, thermals, access and operating discipline.
System boundary
One accountable path from hardware to workload.
We define what X-YORK is responsible for, what the customer controls and what still requires validation.
Engineering layers
What we inspect and configure.
Hardware
PCIe topology, power delivery, cooling, firmware, memory, storage and physical assembly.
Operating system
Linux installation, kernel considerations, remote administration and update planning.
GPU software
NVIDIA drivers, CUDA compatibility, device visibility and container integration.
Workload path
Runtime, model serving or generation stack, storage flow and performance validation.
Delivery standards
Clear scope. Measured results.
Written scope
Configuration, deliverables, timeline and commercial terms are documented before work starts.
Workload validation
Performance is tested against the customer workload and agreed success criteria.
Documented handoff
Customers receive the configuration, operating notes and recommended next steps.
Have an unstable system or an unclear build plan?
Describe the current hardware, software stack and failure mode.