AI Feasibility Studies
AI-accelerated analysis of project feasibility including zoning, costs, and development potential.
Definition
AI Feasibility Studies automate the analysis required to evaluate whether a development project is viable. These tools can quickly analyze zoning regulations, estimate construction costs, calculate development yields, and assess market conditions. By accelerating feasibility analysis from days to hours, AI enables developers and architects to evaluate more sites and scenarios before committing resources to detailed design.
In Depth
Feasibility studies evaluate whether a proposed project is viable before committing significant design resources. AI accelerates the critical analyses — zoning compliance, code-driven building capacity, preliminary cost estimation, and schedule projection — that determine whether the project makes sense to pursue.
The speed advantage is what changes how firms use feasibility analysis. When a feasibility study takes two weeks, firms can only evaluate one or two options. When AI reduces it to two days, firms can evaluate five or six options, selecting the best opportunity from a broader set of possibilities.
Examples
Quickly assessing zoning allowances and development potential for multiple sites
Estimating construction costs during early feasibility based on massing studies
Analyzing parking requirements and their impact on development yield
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
AI Feasibility Studies automate the analysis required to evaluate whether a development project is viable. These tools can quickly analyze zoning regulations, estimate construction costs, calculate development yields, and assess market conditions. By accelerating feasibility analysis from days to hours, AI enables developers and architects to evaluate more sites and scenarios before committing resources to detailed design.
Quickly assessing zoning allowances and development potential for multiple sites. Estimating construction costs during early feasibility based on massing studies. Analyzing parking requirements and their impact on development yield.
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