Data Centers,
End to End.
The AI buildout is the biggest construction program of this decade, and it is being priced with tools built for office parks. This series follows one data center campus through Ruh's platform: raw site to running halls, one project graph, measured at every step.
The workload is different
A campus is the same module, tiled and phased. Price the module wrong once and the error multiplies across every pad and every phase.
The schedule is hostile
Power windows and delivery phases move faster than a manual precon cycle. The team that answers in days loses to the one that answers in hours.
The owner wants receipts
Hyperscale owners audit everything. Every number needs provenance: measured, derived, or assumed, and honest about which.
The series
Why data centers break preconstruction
Campus scale, compressed schedules, and module math that normal estimating was never built for.
Feasibility in an afternoon
Solving a campus on a real site: module pads, circulation spine, substation reservation, delivery phases.
From scheme to drawing set
Data halls, electrical galleries, admin blocks. A drawing set where every dimension knows where it came from.
Takeoff at campus scale
Measure one module honestly, prove it, then let repetition work for you instead of against you.
The estimate an owner can audit
Coverage scores, per-line confidence, and pricing from your own closed jobs. Measured, not guessed.
Bid to build
Sub bids, change orders, and field reports across repeated pads, without re-keying a single number.
One graph to closeout
What the owner sees, phase by phase: one signed record from the first pad to the last handover.
Grounded in the platform, honest about the phase
Ruh's bid-side products ship today: measured takeoffs and priced estimates for the shell, site, and fit-out scopes, running on the project graph. The design phase this series walks, feasibility, generative site schemes on the real parcel, and drawing-set generation, is in preview for data center teams now. Where a part rests on shipped work we say so; where it rests on the preview or the roadmap we say that too, and every derived number carries its provenance.
Building for the AI buildout?
Bring a real site or a real drawing set, and watch the platform run it live. No slideware.