How does
TestFit
Use AI?
Reduces feasibility study cycle time by up to 75% and accelerates deal flow.
Project Overview
Automates real estate site planning using generative AI to instantly create optimized building layouts based on user-defined financial, zoning, and design constraints.
Layman's Explanation
Imagine a super-fast architectural assistant who can instantly sketch hundreds of different building plans for a piece of land. This assistant already knows all the local building rules and your budget, ensuring every sketch is both legal and profitable. You just tell it what you need, and poof, there is the best possible plan, ready in seconds.
Details
TestFit addresses the traditionally slow, manual, and repetitive process of real estate feasibility studies. Its core is a real-time generative AI platform that automates site planning and building design. The technology is centered on a powerful constraint-solving engine that works instantly. Architects, developers, and planners input a wide range of parameters, including zoning data, setbacks, unit mix requirements, parking ratios, and financial targets like yield on cost.
The platform's "Site Solver" AI uses these inputs to generate an optimal, buildable solution that balances all competing constraints. Unlike some tools that produce thousands of options for a user to review, TestFit's primary mode provides a single, best-fit solution that can then be iterated upon in real time. Adjusting any parameter, such as building height or unit count, prompts the AI to instantly regenerate the design, allowing for rapid exploration of possibilities.
A newer generative design feature also allows the AI to autonomously test thousands of site configurations to find optimal outcomes based on user-defined goals. The platform integrates with industry-standard software like Revit and AutoCAD, allowing teams to seamlessly transition from a high-level feasibility study to detailed design. This transforms a process that once took weeks into one that can be done in minutes or hours, enabling faster, data-driven decision-making.
Analogy
TestFit is like a master chef who, instead of you guessing at a recipe, instantly creates the perfect dish based on the ingredients you have (the land), your dietary restrictions (zoning laws), and your budget (financial goals). You can ask for "a little more spice" (more units), and the dish instantly rebalances itself to perfection.
Machine Learning Techniques Used
- Constraint Satisfaction Solving: for its real-time engine that continuously solves complex, multi-variable relationships like zoning compliance, parking ratios, and building typologies.
- Multi-objective Optimization: to simultaneously balance competing goals, such as maximizing unit count while adhering to financial pro forma and design intent.
- Real-time AI System: to instantly reflect user-driven changes to parameters, allowing for immediate feedback and interactive design iteration.
- Data-driven Modeling: to incorporate key data points like zoning regulations, parcel information, and user-defined financial goals directly into the generative process.
More Use Cases in
Construction & Real Estate
Novelty Justification
The project's novelty lies in its sophisticated integration of real-time generative AI with a powerful constraint-solving engine, delivering a single, instantly iterable design solution. This application is at the leading edge of technology adoption within the traditionally slow-moving construction and real estate industry
Project Estimates
