Design generation, space planning, and visualization
AI that generates floor plans, renders designs, and automates architectural documentation. These systems explore thousands of layout options, convert CAD to BIM, and compress timelines—learning from design patterns. The result: faster projects, more design alternatives, and architects focused on high-value decisions.
This application area focuses on rapidly predicting 3D airflow and temperature distributions inside data centers to support design, layout, and cooling decisions. Instead of running full computational fluid dynamics (CFD) models—which can take hours or days—engineers use AI surrogate models to approximate the same results in seconds. These models ingest key parameters such as room geometry, rack placement, server loads, and cooling configurations, and output detailed thermal fields for the entire space. By making thermal simulation effectively real time, organizations can iterate far more quickly on room layouts, capacity expansion plans, and cooling strategies. This leads to better thermal resilience, fewer hotspots, and more efficient use of cooling infrastructure, which directly impacts energy costs and uptime. AI is used to learn a mapping from design and operating conditions to 3D temperature fields based on historical CFD runs or measured data, providing a fast, high-fidelity proxy for traditional simulation workflows.