Sunny Sethi didn't set out to build an AI company when he started designing better fire nozzles in 2020. But the founder of HEN Technologies just closed a $22 million funding round for something far more valuable than hardware - a real-world physics data platform that could reshape how AI systems understand the physical world. What started as a solution to California's wildfire crisis has quietly evolved into a data play that has investors betting big on the intersection of emergency response and machine learning.
HEN Technologies founder Sunny Sethi sounds almost casual when describing how his company increased fire suppression rates by up to 300% while cutting water usage by 67%. It's the kind of breakthrough that would make most founders lean into the pitch, but Sethi is already three steps ahead, focused on what he calls "the muscle on the ground" - and the data goldmine it's creating.
The origin story reads like a pivot born from personal crisis. After earning his PhD at the University of Akron and bouncing through roles at ADAP Nanotech, SunPower, and TE Connectivity, Sethi moved his family from Ohio to California's East Bay in 2013. Then came the megafires - Thomas, Camp, Napa-Sonoma - each one closer, each one more terrifying. In 2019, while Sethi was traveling, his wife faced potential evacuation alone with their three-year-old daughter. Her ultimatum was blunt: "Dude, you need to fix this, otherwise you're not a real scientist."
That challenge launched HEN Technologies in June 2020. With National Science Foundation funding, Sethi dove into computational fluid dynamics research, analyzing how water suppresses fire and how wind disrupts traditional nozzles. The result was hardware that controls droplet size with precision, manages velocity in ways legacy equipment can't, and resists wind interference. In side-by-side comparisons, HEN's nozzles maintain coherent streams while traditional systems disperse - same flow rate, radically different outcomes.
