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

Sunny Sethi, Founder of HEN technologiesdoesn’t sound like someone who has disrupted an industry that has remained largely unchanged since the 1960s. His company builds fire sprinklers – specifically sprinklers that it claims extinguish fires up to three times faster than previous products, while saving 67% of water. But Sethi is down-to-earth about this achievement, more focused on the future than on what has already been done. And what comes next sounds much bigger than jet pipes.

His path to firefighting does not follow a neat narrative. After earning his PhD from the University of Akron, where he researched surfaces and adhesion, he founded ADAP Nanotech, a company that developed a carbon nanotube-based portfolio and won grants from the Air Force Research Lab. He then developed new materials and processes for shingled photovoltaic modules at SunPower. Then, when he joined a company called TE Connectivity, he worked on devices with new adhesive formulations to enable faster production in the automotive industry.

Then came a 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 megafire they thought they would ever see. Then came the Camp Fire and 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 then three-year-old daughter, with no family nearby, facing a possible evacuation order. “She was really mad at me,” Sethi remembers. “She says, ‘Dude, you gotta solve this or you’re not a real scientist.’”

A background spanning nanotechnology, solar energy, semiconductors and the automotive sector had made his thinking ‘free and flexible’, as he puts it. He had seen so many industries, so many different problems. Why not try to solve the problem?

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

In HEN’s comparison video, which Sethi shows me during a Zoom call, the difference is stark. It’s the same flow rate, he says, but HEN’s pattern and speed control keep the flow coherent while traditional nozzles spread out.

But the mouthpiece is just the beginning – what Sethi calls “the muscle on the ground.” HEN has since expanded to include monitors, valves, overhead sprinklers and pressure equipment, and this year is launching a flow control device (“Stream IQ”) and discharge control systems. According to Sethi, each device contains custom-designed circuit boards with sensors and computing power: 23 different designs that turn dumb hardware into smart, connected equipment, some powered by Nvidia Orion Nano processors. In total, Sethi says, HEN has filed 20 patent applications, six of which have been granted so far.

The real innovation is the system these devices create. HEN’s platform uses sensors on the pump that act as a virtual sensor in the nozzle, which keeps track of exactly when the pump is on, how much water flows and what pressure is required. The system records exactly how much water was used in a particular fire, how it was used, which fire hydrant was tapped and what the weather conditions were.

Why it’s important: Fire departments could otherwise run out of water because there is a lack of communication between water suppliers and firefighters. It happened during the Palisades Fire. It happened decades earlier during the Oakland Fire. When two engines are connected to one hydrant, pressure variations can cause one engine to suddenly lose power while the fire continues to grow. In rural America, water tenders, tankers that transport water from distant sources, face their own logistical nightmares. If they can integrate water usage calculations with their own utility monitoring systems to optimize resource allocation, that’s a huge win.

So HEN built a cloud platform with application layers, which Sethi compares to what Adobe did with cloud infrastructure. Consider individual à la carte systems for fire chiefs, battalion chiefs and incident commanders. HEN’s system has weather data; it has GPS on all devices. It can alert those on the front lines that the winds are shifting and they better move their engines, or that a particular fire truck is running low on water.

The Department of Homeland Security, through its ministry, has requested exactly this type of system NERIS programan initiative to apply predictive analytics to emergency operations. ‘But that’s not possible [predictive analytics] unless you have good quality data,” Sethi notes. “You can’t have good quality data unless you have the right hardware.”

If building a predictive analytics platform for emergency response sounds intimidating, Sethi says actually selling it is harder, and he’s most proud of THEM’s traction on that front.

“The hardest part of building this business is that this market is tough because it’s a B2C play if you think about convincing the customers to buy, but the purchasing cycle is B2B,” he explains. “So you really have to create a product that resonates with people – with the end user – but you still have to go through government purchasing cycles, and we’ve cracked both of those.”

The figures confirm this. HEN launched its first products to the market in the second quarter of 2023, lining up 10 fire departments and generating $200,000 in revenue. Then the news started to spread. Sales were $1.6 million in 2024, $5.2 million last year. This year, Hen, which currently has 1,500 fire service customers, expects revenue of $20 million.

Of course, THEM has competition. IDEX Corp, a publicly traded company, sells hoses, mouthpieces and monitors. Software companies like Central Square serve fire departments. A Miami company, First Due, which sells software to public safety agencies, has announced a massive promotion $355 million round last August. But no company “does exactly what we’re trying to do,” Sethi points out.

Anyway, according to Sethi, the limitation is not demand, but scaling up quickly enough. HEN serves the Marine Corps, U.S. military bases, Navy nuclear laboratories, NASA, Abu Dhabi Civil Defense and ships to 22 countries. It operates through 120 distributors and recently qualified for GSA after a year-long vetting process (that’s a federal seal of approval that makes it easier for military and government agencies to purchase).

Fire departments purchase approximately 20,000 new engines each year to replace aging equipment in a national fleet of 200,000, so once THEM are qualified, this becomes recurring revenue (the idea is), and because the hardware generates data, the revenue continues between purchasing cycles.

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

Indeed, it is the software that shows where this gets interesting, because while HEN sells mouthpieces, it collects something more valuable: data. Highly specific, hands-on data on how water behaves under pressure, how flow rates interact with materials, how fire responds to suppression techniques, how physics works in active fire environments.

It’s exactly what companies building so-called world models need. These AI systems that construct simulated representations of physical environments to predict future states require real-world, multimodal data from physical systems under extreme conditions. You can’t just teach AI about physics through simulations. You need what THEM collects on each bet.

Sethi doesn’t want to elaborate, but he knows what he’s up against. Companies that train robotics and predictive physics engines would pay handsomely for this kind of real-world physics data.

Investors see it too. Last monthHEN closed a $20 million Series A round, plus $2 million in venture capital debt from Silicon Valley Bank. O’Neil Strategic Capital led the financing, which included NSFO, Tanas Capital and z21 Ventures. The round brought the company’s total funding to more than $30 million.

Sethi is already looking ahead. He says the company will raise funds again in the second quarter of this year.