Think of this as using smart algorithms as a co-designer that helps architects and interior designers create greener, more energy-efficient buildings and spaces—suggesting layouts, materials, and systems that reduce waste and environmental impact.
Traditional building and interior design rely heavily on manual calculations and intuition to achieve sustainability goals, which is slow, error-prone, and often fails to optimize across energy use, materials, cost, and comfort simultaneously. AI-aided design can explore many more design options and automatically optimize for sustainability constraints.
Domain-specific design data (past projects, performance outcomes), integrated workflows with existing CAD/BIM tools, and proprietary optimization formulations for sustainability metrics can all create defensibility.
Hybrid
Structured SQL
High (Custom Models/Infra)
Computational cost for running large-scale design simulations and multi-objective optimization across many candidate designs.
Early Majority
Focuses explicitly on AI-driven sustainability optimization in the design loop, rather than generic CAD/BIM automation, enabling multi-objective tradeoffs between energy, cost, materials, and comfort from very early design stages.