Think of this as a smart design assistant for architects that explores many different building options on a computer—like trying thousands of Lego arrangements—to find layouts and shapes that are more sustainable, energy‑efficient, and comfortable before anything is built in the real world.
Traditional sustainable design relies on slow, manual iteration and expert intuition; this approach uses intelligent computational exploration to automatically generate, simulate, and compare many alternative design options so architects can reach higher‑performing, greener designs faster and with more confidence.
Tight integration of domain-specific sustainability knowledge, simulation workflows, and design constraints into a repeatable exploration pipeline that becomes more valuable as project and performance data accumulate.
Hybrid
Unknown
High (Custom Models/Infra)
Simulation and optimization cost as the number of design parameters, performance objectives, and explored variants grows; integration overhead with existing CAD/BIM workflows.
Early Adopters
Focus on intelligent exploration specifically tuned for sustainable design objectives (e.g., energy, daylight, material impact) rather than generic architectural optimization, enabling architects to interrogate environmental trade-offs more systematically during early-stage design.