AI Biotech Facility Planning
The Problem
“Biotech facility planning is slow, costly, error-prone”
Organizations face these key challenges:
1
Unstructured tenant/user requirements lead to missed critical constraints (air changes, redundancy, exhaust, hazardous storage, vibration/EMI limits) and late-stage redesigns
2
Limited visibility into building/utility feasibility (power, chilled water, steam, exhaust routing, roof loading, floor-to-floor height) causes costly surprises after LOI
3
Fragmented data across brokers, architects, engineers, GC estimates, and permitting consultants makes benchmarking inconsistent and slows decision-making
Impact When Solved
Faster go/no-go decisions with automated feasibility scoring and risk flags across candidate sitesMore accurate early capex/opex and schedule forecasts with scenario-based sensitivity analysis (utility upgrades, redundancy levels, cleanroom classes)