Custom AI notes from the shop floor.
Practical writing on AI hardware, open-weight models, evaluation and the systems we build, from the engineers who build them.
From the bench.
Sizing GPU Capacity by Team Size and Active Use
How to size on-prem GPU volume by seat count, concurrency and active use patterns, so your AI hardware matches real team load without overbuying.
What Breaks in the First 90 Days of On-Premises AI
The real failure modes in the first 90 days of on-premises AI, what each one costs to fix, and the scoping decisions that stop them happening.
How Many GPUs Will I Need for Custom AI
Work out how many GPUs your custom AI workload actually needs, from model size and concurrency to VRAM headroom, without over-buying hardware you will not use.
Buy or Lease GPU Servers for On-Premises AI
How to decide between buying, leasing or financing GPU servers for on-premises AI, with the tax, refresh cycle and utilization trade-offs that move the number.
Spec your system.
Tell us the models you want to run, how many people will use them and where the hardware should live. An engineer replies with a first configuration and the questions that decide the quote.