Sunny Sethi, founder of HEN Technologies, doesn’t sound like someone who’s disrupted an industry that has remained largely unchanged since the 1960s. His company builds fire nozzles — specifically, nozzles that it says increase suppression rates by up to 300% while conserving 67% of water. But Sethi is matter-of-fact about this achievement, more focused on what’s next than what’s already been done. And what’s next sounds a lot bigger than fire nozzles.

His path to firefighting doesn’t follow a tidy narrative. After nabbing his PhD at the University of Akron, where he researched surfaces and adhesion, he founded ADAP Nanotech, an outfit that developed a carbon nanotube-based portfolio and won Air Force Research Lab grants. Next, at SunPower, he developed new materials and processes for shingled photovoltaic modules. When he landed next at a company called TE Connectivity, he worked on devices with new adhesive formulations to enable faster manufacturing 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’d ever see, 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 then three-year-old daughter, no family nearby, facing a potential evacuation order. “She was really mad at me,” Sethi recalls. “She’s like, ‘Dude, you need to fix this, otherwise you’re not a real scientist.’”

A background spanning nanotechnology, solar, semiconductors, and automotive had made his thinking “bias free and flexible,” as he puts it. He’d seen so many industries, so many different problems. Why not try to fix the problem?

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

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

But the nozzle is just the beginning — what Sethi calls “the muscle on the ground.” HEN has since expanded into monitors, valves, overhead sprinklers, and pressure devices, and is launching a flow-control device (“Stream IQ”) and discharge 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 hardware into smart, connected equipment, some powered by Nvidia Orion Nano processors. Altogether, says Sethi, HEN has filed 20 patent applications with half a dozen granted so far.

The real innovation is the system these devices create. HEN’s platform uses sensors at the pump to act as a virtual sensor in the nozzle, tracking exactly when it’s on, how much water flows, and what pressure is required. The system captures precisely how much water was used for a given fire, how it was used, which hydrant was tapped, and what the weather conditions were.

Why it matters: Fire departments can run out of water otherwise, because there’s no communication between water suppliers and firefighters. It happened in the Palisades Fire. It happened in the Oakland Fire decades earlier. When two engines are connected to one hydrant, pressure variations can mean that one engine suddenly gets nothing as a fire continues to grow. In rural America, water tenders, which are tankers shuttling 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 giant win.

So HEN built a cloud platform with application layers, which Sethi likens to what Adobe did with cloud infrastructure. Think Individual à la carte systems for fire captains, battalion chiefs, and incident commanders. HEN’s system has weather data; it has GPS in all devices. It can warn those on the front lines that the wind is about to shift and they’d better move their engines, or that a particular fire truck is running out of water.

The Department of Homeland Security has been asking for exactly this kind of system through its NERIS program, which is an initiative to bring predictive analytics to emergency operations. “But you can’t have [predictive analytics] unless you have good quality data,” Sethi notes. “You can’t have good quality data unless you have the right hardware.”

HEN isn’t monetizing that data yet. It’s implementing data nodes, putting devices in as many systems as possible, building the data pipeline, creating the data lake. Next year, says Sethi, it will start commercializing the application layer with its built-in intelligence.

If building a predictive analytics platform for emergency response sounds daunting, Sethi says actually selling it is tougher, and he’s proudest of HEN’s traction on that front.

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

The numbers bear this out. HEN launched its first products into the market in the second quarter of 2023, lining up 10 fire departments and generating $200,000 in revenue. Then word started to spread. Revenue hit $1.6 million in 2024, then $5.2 million last year. This year, Hen, which currently has 1,500 fire department customers, is projecting $20 million in revenue. 

HEN has competition, of course. IDEX Corp, a public company, sells hoses, nozzles, and monitors. Software companies like Central Square serve fire departments. A Miami company, First Due, which sells software to public safety agencies, announced a massive $355 million round last August.  But no company is “doing exactly what we are trying to do,” insists Sethi.

Still, Sethi says that the constraint isn’t demand — it’s scaling fast enough. HEN serves the Marine Corps, US Army bases, Naval atomic labs, NASA, Abu Dhabi Civil Defense, and ships to 22 countries. It works 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 buy).

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

HEN’s dual goal has required building a very specific team. Its software lead was formerly 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 from Tesla, Apple, and Microsoft. “If you ask me technical questions, I would not be able to answer everything,” Sethi admits with a laugh, “but I have such good teams that [it] has been a blessing.”

Indeed, it’s the software that hints at where this gets interesting, because while HEN is selling nozzles, it’s amassing something more valuable: data. Highly specific, real-world data about 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 teach AI about physics through simulations alone. You need what HEN collects with every deployment.

Sethi won’t elaborate, but he knows what he’s sitting on. Companies training robotics and predictive physics engines would pay handsomely for this kind of real-world physics data.

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

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