Inviscid AI builds physics-informed AI that creates digital twins to simulate building performance in real time. The platform combines IoT sensor data with computational fluid dynamics modeling to autonomously optimize facility operations. It improves airflow patterns, eliminates dead zones, reduces HVAC power consumption, and lowers cooling costs while maintaining thermal comfort and air quality. The company targets industrial facilities and data centers with a physics-first approach to how air, heat, and energy move through buildings.
Inviscid AI
ActiveReal-time Physics Simulations for Industrial Facilities & Data Centers
Total raised
$500K
1 round
Stage
Seed
Jan 2026
Team
1-10
since 2026
Pricing
—
Founded
2026
Agent-ready
—
Real-time physics simulations of airflow, heat, and energy movement through buildings
Digital twins that mirror live facility conditions
Computational fluid dynamics (CFD) modeling for thermal and airflow analysis
Integration of IoT sensor data into the simulation layer
Autonomous optimization of facility cooling and HVAC operations
Identification and elimination of airflow dead zones
HVAC power consumption and cooling cost reduction
Thermal comfort and air quality maintenance
12/100
Early
MCP server
Public API
Webhooks
OAuth 2.0
SDKs
No public agent surfaces detected yet.
Jan 2026 Seed $500K ● Y Combinator
Capital network
$500K raised ·1 backer·10 network links
- Backers1
- Shared portfoliocompanies these backers also fund
- Extended networkfunds that co-invest alongside them
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- What kind of simulation does Inviscid AI use?
- It uses computational fluid dynamics (CFD) modeling combined with physics-informed AI to simulate how air, heat, and energy move through a building in real time.
- What types of facilities does it target?
- Inviscid AI focuses on industrial facilities and data centers, where cooling and HVAC energy represent significant operating costs.
- Does it require IoT sensors?
- Yes. The platform combines IoT sensor data with CFD modeling to keep the digital twin synchronized with real conditions and to drive optimization.
- What outcomes does the platform aim to deliver?
- It aims to improve airflow patterns, eliminate dead zones, reduce HVAC power consumption, and lower cooling costs while maintaining thermal comfort and air quality.
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