AI R&D Facility Planning
The Problem
“Faster, more accurate R&D facility planning decisions”
Organizations face these key challenges:
1
Uncertain forecasts for AI headcount, compute growth, and specialized lab needs cause repeated rework and mis-sized facilities
2
Critical infrastructure constraints (power availability, redundancy, cooling, floor loading, vibration, and security zoning) are hard to validate early and are often discovered late
3
Data is fragmented across brokers, architects, engineers, utilities, and internal teams, leading to slow decision cycles and inconsistent assumptions
Impact When Solved
30–50% faster site selection, feasibility, and test-fit iteration through automated scenario generation and constraint checking10–20% reduction in change orders and redesign by surfacing power/cooling/permitting infeasibilities before lease signing or design development