This founder cracked firefighting — now he’s creating an AI gold mine

Sunny Sethi, founder of HEN Technologies, doesn’t sound like someone who has revolutionized an industry that has remained largely unchanged since the 1960s. His company makes fire nozzles — specifically, nozzles that it says extinguish fires up to three times faster than previous products while conserving 67% more water. But Sethi talks about this achievement realistically, focusing more on what is to come than on what has already been accomplished. And what’s next looks much larger than fire craters.

His path to firefighting doesn’t follow a neat narrative. After earning his PhD from the University of Akron, where he conducted research on surfaces and adhesion, he founded ADAP Nanotech, a company that developed a portfolio based on carbon nanotubes and received grants from the Air Force Research Laboratory. Then, at SunPower, he developed new materials and processes for wood-panel PV modules. When he later arrived at a company called TE Connectivity, he worked on devices with new adhesive formulations to enable faster manufacturing in the automotive industry.

Then came the challenge from his wife. The two had moved from Ohio to the East Bay outside San Francisco in 2013. A few years later, came the Thomas Fire — the only huge fire they’d ever seen, they thought. Then came the Camp Fire, then the Napa-Sonoma fires. The breaking point came in 2019. Sethi was traveling during evacuation warnings while his wife was home alone with their three-year-old daughter, with no family nearby, and facing a potential evacuation order. “She was really mad at me,” Sethi recalls. “It says, ‘Dude, you need to fix this, or you won’t be a real scientist.’”

His background spanning nanotechnology, solar energy, semiconductors, and automotive made his thinking “bias-free and flexible,” he says. He has seen many industries, many different problems. Why no Trying to solve the problem?

In June 2020, he founded HEN Technologies (High Efficiency Nozzles) in nearby Hayward. With funding from the National Science Foundation, he conducted research in computational fluid dynamics, analyzing how water suppresses fire and how wind affects it. The result: a nozzle that precisely controls droplet size, manages its speed in new ways, and resists wind.

In HEN’s comparison video, which Sethi showed me over a Zoom call, the difference is stark. It’s the same flow rate, he says, but the HEN pattern and speed control keep the stream consistent while traditional nozzles disperse.

But the nozzle is just the beginning, what Sethi calls “the muscle on the floor.” HEN has since expanded to include monitors, valves, overhead sprayers and pressure devices, and is launching its flow controller (“Stream IQ”) and vacuum control systems this year. According to Sethi, each device contains custom-designed circuit boards with sensors and computing power — 23 different designs that turn dumb devices into smart, connected equipment, some of which are powered by Nvidia Orion Nano processors. HEN has filed 20 patent applications, of which six have been accepted so far, says Sethi.

The real innovation is the system these devices create. The HEN platform uses sensors in the pump to act as a virtual sensor in the nozzle, tracking exactly when it is running, how much water is flowing, and what pressure is needed. The system accurately captures how much water was used on a given fire, how it was used, what tap was tapped, and what the weather conditions were.

Why this is important: Fire departments can run out of water because there is no communication between water suppliers and firefighters. It happened in the Palisades fire. It happened in the Oakland fire decades ago. When two engines are connected to one hydrant, pressure differences can mean the engine suddenly stops running as the fire continues to grow. In rural America, water tenders, which are tankers that transport water from distant sources, face their own logistical nightmares. If they can integrate water use calculations with their utility monitoring systems to improve resource allocation, that would be a big win.

So HEN built a cloud platform with layers of applications, which Sethi likens to what Adobe did with cloud infrastructure. Consider individual selective systems for fire chiefs, battalion chiefs and incident commanders. The HEN system contains weather data. It has GPS in all devices. It can warn those on the front lines that the winds are about to shift and they’d better rev their engines, or that a particular fire truck is running out of water.

The Department of Homeland Security requested exactly this type of system through its NERIS program, an initiative to provide predictive analytics for emergency operations. “But you can’t have it [predictive analytics] “Unless you have good quality data,” Sethi points out, “you can’t get good quality data unless you have the right hardware.”

If building a predictive analytics platform for emergency response sounds daunting, Sethi says it’s actually an even harder sell, and he’s proud of HEN’s success on that front.

“The hardest part about building this company is that this market is tough because it’s a business-to-consumer game when you think about convincing customers to buy, but the buying cycle is business-to-business,” he explains. “So you have to make a product that resonates with people — with the end user — but you still have to go through government procurement cycles, and we’ve solved both of those things.”

The numbers bear this out. HEN launched its first products on the market in the second quarter of 2023, equipping 10 fire departments and generating revenues of $200,000. Then the news started spreading. Revenues reached $1.6 million in 2024, then $5.2 million last year. This year, Hen, which currently has 1,500 fire department clients, expects $20 million in revenue.

HEN has competition, of course. IDEX Corp., a publicly traded company, sells hoses, nozzles and screens. Software companies like Central Square serve fire departments. Miami-based First Due, which sells software to public safety agencies, announced a massive $355 million round last August. But no company “does exactly what we’re trying to do,” Sethi insists.

However, Sethi says the hurdle is not demand, but scaling fast enough. HEN serves the Marine Corps, US Army bases, Naval Atomic Laboratories, NASA, and Abu Dhabi Civil Defense, and ships to 22 countries. It operates through 120 distributors and was recently GSA qualified after a year-long inspection process (this is a federal seal of approval that makes it easier for military and government agencies to purchase).

Fire departments buy about 20,000 new engines each year to replace aging equipment in a national fleet of 200,000 engines, so once a HEN qualifies, it becomes recurring revenue (that’s the idea), and because the devices generate data, the revenue continues between purchase cycles.

HEN’s dual goal requires very specific team building. The software lead was previously a senior manager who helped build Adobe’s cloud infrastructure. Other members of the 50-person HEN team include a former NASA engineer and veterans of Tesla, Apple and Microsoft. “If you asked me technical questions, I wouldn’t be able to answer everything,” Sethi admits with a laugh, “but I have such good teams that I [it] “It was a blessing.”

In fact, it’s the software that hints at where this gets interesting, because while HEN sells nozzles, it collects something much more valuable: data. Highly specific factual data about how water behaves under pressure, how flow rates interact with materials, how fires respond to suppression techniques, and how physics works in active fire environments.

This is exactly what companies building so-called global models need. These AI systems, which build simulated representations of physical environments to predict future states, require realistic, multimodal data from physical systems under extreme conditions. You can’t teach AI about physics through simulations alone. You need what HEN collects with every deployment.

Sethi won’t go into detail, but he knows what he’s sitting on. Companies that train robots and predictive physics engines will pay big bucks for this kind of real-world physics data.

Investors see that too. Last month, HEN closed a $20 million financing round, in addition to $2 million in venture debt from Silicon Valley Bank. O’Neil Strategic Capital led the financing, with participation from NSFO, Tanas Capital and z21 Ventures. The round brought the company’s total funding to more than $30 million.

Meanwhile, Sethi is already looking ahead. He says the company will return to fundraising in the second quarter of this year.