Making Margin in the Inference Era
Eight plays for standing up capacity, running it profitably, and scaling without a rebuild.
Of the 100-plus AI clouds operating today, only 10 to 15 run at real scale. GPU availability isn’t what separates them — supply is normalizing, token pricing is public, energy costs are climbing. What’s left is architecture.
We build the data platform inside AI clouds you already know, including CoreWeave, Nebius, Oracle Cloud Infrastructure, and more. We don’t run an AI cloud. You do. But we’ve watched enough operators hit the same walls to know which decisions look right at 500 GPUs and get expensive at 5,000.
This playbook is those decisions, staged the way you’ll meet them: standing up capacity, running it profitably, scaling it without a forced migration.
Inside, you’ll find:
- Why GPU utilization can be a misleading measure and the goodput scorecard that replaces it
- How one operator went from ~600 concurrent users to 5,000+ on the same 72 GPUs
- The re-architecture trap, and the pre-mortem that keeps you out of it
- The nine questions enterprise tenants will be asking by 2027
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