Sunny Sethi, its founder HEN Technologiesdoesn’t sound like someone who has disrupted an industry that has remained largely unchanged since the 1960s. His company makes fire nozzles – specifically, nozzles that he says increase suppression rates by up to 300% while saving 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 follows sounds much bigger than fire nozzles.
His path to firefighting doesn’t follow a neat narrative. After earning his PhD at the University of Akron, researching surfaces and adhesion, he founded ADAP Nanotech, a group that developed a portfolio based on carbon nanotubes and won grants from the Air Force Research Laboratory. Then at SunPower, he developed new materials and processes for shingle photovoltaic cells. When he next landed 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 of San Francisco in 2013. A few years later came the Thomas Fire — the only megfire they’d ever seen, they thought. Then came the Camp Fire, then the Napa-Sonoma fires. Then, in 2019, came the tipping point. Setty 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 angry with me,” Shetty recalls. “He’s telling me, man, you’ve got to fix this or you’re not a real scientist.”
A background spanning nanotechnology, solar energy, semiconductors and the automotive industry 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 fix the problem?
In June 2020, he founded HEN Technologies 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 controls droplet size precisely, manages velocity in new ways, and resists wind.
In the HEN comparison video, which Sethi shows me via a Zoom call, the difference is stark. It’s the same flow rate, he says, but the HEN’s design and speed control keep the flow consistent while traditional nozzles scatter.
But the nozzle is just the beginning – what Sethi calls “the muscle on the ground.” Since then, HEN has expanded into monitors, valves, air flow nozzles and pressure devices, 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 gear, some powered by Nvidia Orion Nano processors. In all, Sethi says, HEN has filed 20 patent applications with half a dozen granted so far.
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The real innovation is the system these devices create. HEN’s platform uses sensors on the pump to act as a virtual sensor on the nozzle, monitoring exactly when it is on, how much water is flowing and what pressure is required. The system accurately records how much water was used for a given fire, how it was used, which hydrant was used and what the weather conditions were.
Why it matters: Fire services can otherwise run out of water because there is no communication between water suppliers and firefighters. It happened in the Palisades fire. It happened at the Oakland Fire decades earlier. When two engines are connected to a hydrant, the pressure fluctuations can mean that one engine suddenly gets nothing 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 own utility monitoring systems to optimize resource allocation, that’s a huge win.
So HEN created a cloud platform with application layers, which Sethi likens to what Adobe did with cloud infrastructure. Consider individual à la carte systems for firefighters, battalion chiefs and incident commanders. HEN’s system has weather data. has GPS on all devices. It can warn those on the front lines that the wind is about to shift and they better start their engines, or that a particular fire truck is running out of water.
The Department of Homeland Security has requested just this type of system through it NERIS programwhich is an initiative to provide predictive analytics to emergency operations. “But you can’t have [predictive analytics] unless you have good quality data,” notes Sethi. “You can’t have good quality data if you don’t have the right hardware.”
HEN is not yet monetizing this data. It implements data nodes, places devices in as many systems as possible, builds the data line, creates the data lake. Next year, Sethi says, it will begin commercializing the application layer with its embedded intelligence.
If building a predictive analytics platform for emergency response sounds daunting, Sethi says selling it is actually harder, and he’s proud of HEN’s traction on that front.
“The hardest part of building this company is that this market is difficult because it’s a B2C game when you think about getting customers to buy, but the procurement cycle is B2B,” he explains. “So you have to really build a product that resonates with people – with the end user – but you still have to go through government buying cycles, and we’ve broken both of those.”
The numbers confirm it. HEN brought its first products to market in the second quarter of 2023, lining up 10 fire departments and generating $200,000 in revenue. Then the news began to spread. Revenue reached $1.6 million in 2024, up from $5.2 million last year. This year, Hen, which currently has 1,500 fire department customers, projects $20 million in revenue.
HEN has competition of course. IDEX Corp, a public company, sells hoses, nozzles and screens. 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’re trying to do,” Sethi insists.
However, Sethi says the limitation isn’t demand — it’s escalating quite quickly. HEN serves the Marine Corps, US Army bases, Naval Atomic Laboratories, NASA, Abu Dhabi Civil Defense and ships in 22 countries. It operates through 120 distributors and was recently GSA certified after a year-long review process (this is a federal seal of approval that makes it easier for military and government agencies to buy).
Fire services buy around 20,000 new engines each year to replace old equipment in a national fleet of 200,000, so when HEN is certified it becomes recurring revenue (that’s the idea) and because the hardware generates data, the revenue continues between purchase cycles.
The dual objective of HEN requires the creation of a very specific team. Its chief software officer was formerly a senior manager 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 wouldn’t be able to answer them all,” Shetty admits with a laugh, “but I have such good teams that [it] it was a blessing.”
Indeed, it’s the software that indicates where this gets interesting, because while HEN sells nozzles, it collects something more valuable: data. Highly specific, real data about how water behaves under pressure, how flow rates interact with materials, how fire responds to suppression techniques, how physics work in active fire environments.
It is exactly what the companies that make the so-called global models need. These artificial intelligence systems that construct simulated representations of natural environments to predict future states require real, multimodal data from natural 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 that train robotics and physics prediction 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 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.
Shetty, meanwhile, is already looking ahead. He says the company will return to fundraising in the second quarter of this year.
