Hardware + software
The machines, the GPUs, and the software to run them.
The engagement, in one paragraph
We spec, source, and configure local inference machines and edge devices, then install the complete software stack on top. GPU sizing is based on measured workload requirements, not brochure numbers, so you buy enough hardware and no more.
Standard for every engagement
What you receive
The deliverables.
Workload analysis and GPU sizing recommendation
Hardware bill of materials at two or three price points
Configured inference stack with monitoring and alerting
Edge-device setup for on-site or offline use
Benchmarks proving the machine meets the requirement
Fit check
Signs you need this.
A vendor quote smells like it was sized to their margin, not your load
You need inference at the edge, on-site, or fully offline
Cloud GPU bills are becoming a line item finance asks about
You want to own the capability instead of renting it forever
None of these fit?
Briefs arrive in every shape. Describe the problem in plain language, the scoping step exists to find the right service, including when the right answer is none of them.
Machines & stack