Test fit analysis is the process of determining whether and how a proposed building program can physically fit on a development site within zoning and regulatory constraints. It includes massing studies, floor plate layouts, parking configurations, unit mix optimization, and preliminary site planning. AI tools can now generate and evaluate multiple test fit scenarios rapidly, accelerating early-stage development feasibility.
A test fit analysis examines: building footprint and massing within zoning envelopes, floor plate efficiency and layout options, parking requirements and configuration (structured, surface, underground), unit mix and size optimization (for residential), tenant layout options (for office and industrial), site circulation, loading, and access, open space and amenity requirements, and code compliance (fire access, egress, ADA).
Traditional test fits require architects to manually draft and iterate on layouts — a process that takes days per scenario. AI-powered test fit tools can generate dozens of compliant scenarios in minutes, optimize for different objectives (maximize units, maximize rentable area, minimize construction cost), and quickly identify the development program that maximizes financial returns within physical constraints.
Zoning analysis is the process of evaluating a property's zoning designation, permitted uses, development standards (height, density, setbacks, parking), overlay districts, and entitlement requirements to determine what can be built and what approvals are needed. AI-powered zoning analysis automates the review of complex municipal codes and identifies development constraints and opportunities faster than manual research.
AI underwriting in commercial real estate uses artificial intelligence to automate the financial modeling, sensitivity analysis, and return projections that inform investment and development decisions. AI underwriting systems can produce institutional-grade financial models in minutes — incorporating market data, comparable transactions, construction cost estimates, and financing assumptions.
AI site selection uses artificial intelligence to identify, evaluate, and rank potential development sites across large geographic areas. By processing thousands of parcels against zoning, environmental, infrastructure, demographic, and financial criteria simultaneously, AI site selection compresses what traditionally takes months of manual research into days.