Real-time Building Simulations to Optimize Energy and Operationalβ¦
Company is active
Event Year: 2026
Company is active
Event Year: 2026
Inviscid AI is revolutionizing building and data center operations through physics-informed AI solutions. By integrating real-time IoT sensor data with advanced computational fluid dynamics (CFD) modeling, Inviscid AI constructs digital twins that accurately simulate building performance in real-time, enabling autonomous operational optimization.
Our platform focuses on optimizing airflow patterns and ventilation strategies to eliminate stagnant zones, enhance air distribution, and reduce the strain on mechanical systems. This leads to minimized HVAC power consumption, reduced cooling costs, and lower overall operational expenses, all while maintaining optimal thermal comfort and superior indoor air quality. Furthermore, we optimize equipment scheduling and maintenance cycles by predicting system behavior under various conditions, empowering facilities managers to proactively address potential issues before they escalate.
Our physics-first methodology ensures that optimization is not solely based on historical data patterns, but rather on a profound understanding of air, heat, and energy dynamics within the building. This approach allows us to identify innovative solutions that traditional rule-based or purely data-driven systems might overlook, resulting in more effective and sustainable building management.
Inviscid AI is revolutionizing building and data center operations through physics-informed AI solutions. By integrating real-time IoT sensor data with advanced computational fluid dynamics (CFD) modeling, Inviscid AI constructs digital twins that accurately simulate building performance in real-time, enabling autonomous operational optimization.
Our platform focuses on optimizing airflow patterns and ventilation strategies to eliminate stagnant zones, enhance air distribution, and reduce the strain on mechanical systems. This leads to minimized HVAC power consumption, reduced cooling costs, and lower overall operational expenses, all while maintaining optimal thermal comfort and superior indoor air quality. Furthermore, we optimize equipment scheduling and maintenance cycles by predicting system behavior under various conditions, empowering facilities managers to proactively address potential issues before they escalate.
Our physics-first methodology ensures that optimization is not solely based on historical data patterns, but rather on a profound understanding of air, heat, and energy dynamics within the building. This approach allows us to identify innovative solutions that traditional rule-based or purely data-driven systems might overlook, resulting in more effective and sustainable building management.
Total Raised: Unknown (Y Combinator backed)
Last Round: Winter 2026
Total Raised: Unknown (Y Combinator backed)
Last Round: Winter 2026
B2B
B2B
B2B -> Engineering, Product and Design
B2B -> Engineering, Product and Design
Team size: 2
Hiring: No
Team size: 2
Hiring: No