Inviscid AI provides AI cooling simulations for HVAC and thermal optimization across buildings and data centers. The site says its physics-based simulations run 1000 times faster than traditional CFD and push setpoint recommendations into building management systems. It reports portfolio-wide energy cost reductions above 36 percent and cites deployment-to-ROI timelines under 90 days.
Optimize HVAC vent placement to improve air circulation; Validate sea wall designs through multiple iterations; Forecast storm surge for water management infrastructure; Enhance energy system performance with real-time data; Monitor building systems continuously with AI
Co-Founder
Inviscid AI offers a cutting-edge real-time building intelligence platform that significantly accelerates building simulations by 1000 times using neural networks that adhere to physical laws. Their main product offerings include:
Neural Network Simulation: This technology models building systems while respecting fundamental physical laws, ensuring that the predictions made are physically plausible and reliable.
Building Management System (BMS) Integration: Inviscid AI's platform integrates seamlessly with existing building management systems, allowing for real-time optimization of various building operations.
IoT Sensor Processing: The platform processes data from thousands of IoT sensors, optimizing HVAC (heating, ventilation, and air conditioning) and lighting systems to enhance energy efficiency and operational performance.
Airflow Simulation: Their technology transforms weeks of computational fluid dynamics (CFD) simulations into seconds, enabling rapid analysis and decision-making.
Key Features and Benefits:
Overall, Inviscid AI's offerings are designed to empower building management professionals and engineers in infrastructure design, making their processes faster, more efficient, and more effective.
Serves clients with measurable impacts; Achieved 240x faster HVAC optimization; Validated designs through 150+ iterations; Demonstrated 600x faster storm surge forecasting