Sunny Sethi, founder of HEN Technologies, doesn’t sound like someone who would shake up an industry that hasn’t changed much since the 1960s. His company manufactures firefighting nozzles, specifically nozzles, that he says save water by 67% while increasing firefighting speeds by up to 300%. But Sethi is matter-of-fact about this accomplishment, focusing more on what comes next rather than what’s already been done. And the next sound is much louder than the fire nozzle.
His path to becoming a firefighter does not follow a neat narrative. After earning his PhD in surface and adhesion research at the University of Akron, he developed a carbon nanotube-based portfolio and founded ADAP Nanotech, which received an Air Force Research Laboratory grant. Next, at SunPower, he developed new materials and processes for shingled photovoltaic modules. When he next joined a company called TE Connectivity, he worked on devices that used new adhesive formulations to enable faster manufacturing in the automotive industry.
Then a challenge came from my wife. The couple moved from Ohio to the East Bay outside San Francisco in 2013. A few years later, they thought, there was the Thomas Fire, the only major fire they had ever seen. Then there was the Camp Fire, and then there was the Napa-Sonoma fire. Then, in 2019, a breaking point came. Sethi was traveling during the evacuation warning and his wife had no family nearby, so they were home alone with their then-3-year-old daughter and were likely to be ordered to evacuate. Sethi recalls: “She was really mad at me. “She was like, ‘Hey, you need to fix this. ‘If you don’t, you’re not a real scientist.’”
His background in nanotechnology, solar, semiconductors and automobiles makes his thinking “unbiased and flexible.” He saw so many industries and so many different problems. why ~ no Trying to solve a problem?
In June 2020, he founded HEN Technologies, a high-efficiency nozzle specialist, near Hayward. With funding from the National Science Foundation, he conducted computational fluid dynamics research to analyze how water suppresses fires and how wind affects fires. The result is a nozzle that precisely controls droplet size, manages velocity in new ways, and resists wind.
In the HEN comparison video that Sethi showed me over a Zoom call, the difference is stark. He says the flow rate is the same, but HEN’s pattern and velocity control keeps the stream consistent while traditional nozzles disperse.
But nozzles are just the beginning. Sethi calls them “muscles of the earth.” HEN has since expanded into monitors, valves, overhead sprinklers and pressure devices, and plans to launch a flow control device (“Stream IQ”) and discharge control system this year. According to Sethi, each device contains a custom-designed circuit board with sensors and computing power. That means 23 different designs that turn dumb hardware into smart, connected devices, some powered by the Nvidia Orion Nano processor. Sethi said HEN has so far applied for 20 patents and six have been approved.
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The real innovation is the systems these devices create. HEN’s platform uses sensors on the pump to act as a virtual sensor for the nozzle, accurately tracking when the pump is on, how much water is being pumped, and how much pressure is needed. The system captures exactly how much water was used on a particular fire, how it was used, which hydrants were used and what the weather conditions were.
Why it matters: Fire departments can run out of water because there is no communication between water suppliers and firefighters. The Palisade fire incident occurred. This is what happened with the Oakland fires decades ago. If two engines are connected to one fire hydrant, one engine may suddenly be left with nothing as the fire continues to grow due to pressure changes. In rural America, water suppliers – tankers transporting water from distant locations – face a logistical nightmare. If you can optimize resource allocation by integrating water usage calculations with your own utility monitoring system, that’s a big win.
So HEN built a cloud platform with an application layer, which Sethi likened to what Adobe did with its cloud infrastructure. Consider individually tailored systems for fire chiefs, battalion commanders, and incident commanders. HEN’s system has weather data. Every device has GPS. It might warn people on the front lines that the wind will soon change and it would be better to move the engines, or that a particular fire truck is running low on water.
The Department of Homeland Security has been calling for exactly this kind of system through its NERIS program, an initiative to apply predictive analytics to emergency operations. “But you can’t do predictive analytics without good quality data,” says Sethi. “You can’t get good quality data without the right hardware.”
HEN does not yet monetize this data. Implement data nodes, deploy devices on as many systems as possible, build data pipelines, and create a data lake. Sethi said he expects to begin commercialization of the application layer with embedded intelligence next year.
If building a predictive analytics platform for emergency response sounds difficult, it’s actually harder to sell, says Sethi, who says he’s most proud of HEN’s traction in that space.
“The hardest part about setting up this company is that although we are a B2C play when it comes to convincing customers to buy, our procurement cycle is B2B, so this market is difficult,” he explains. “So you have to create a product that resonates with people, the end users, but you still have to go through the government purchasing cycle, and we’ve solved both of those.”
The numbers back this up. HEN brought its first product to market in the second quarter of 2023, serving 10 fire departments and generating $200,000 in revenue. Then rumors began to spread. Sales recorded $1.6 million in 2024 and $5.2 million last year. Hen, which currently has 1,500 fire department customers, expects revenue of $20 million this year.
Of course, HEN has competition. IDEX Corp, a public company, sells hoses, nozzles and monitors. Software companies like Central Square provide services to fire departments. First Due, a Miami company that sells software to public safety agencies, announced a major investment of $355 million in August. But no company, Sethi argues, “does exactly what we’re trying to do.”
Still, Sethi says the pharma is expanding fast enough, not just demand. HEN serves the Marine Corps, U.S. Army bases, the Naval Atomic Laboratory, NASA, the Abu Dhabi Civil Defense, and ships to 22 countries. It operates through 120 distributors and recently went through a year-long screening process to earn GSA status (a federal stamp of approval that makes it easier for military and government agencies to purchase).
Fire departments purchase about 20,000 new engines each year to replace aging equipment in 200,000 vehicles across the country, so if HEN qualifies, it becomes recurring revenue (the idea), and because the hardware generates data, the revenue continues between purchase cycles.
HEN’s dual goals required a very specific team composition. The head of software was previously a senior executive who helped build Adobe’s cloud infrastructure. Other members of HEN’s 50-person team include former NASA engineers and veterans from Tesla, Apple, and Microsoft. Sethi admitted with a smile. “If you ask a technical question, I can’t answer everything, but I’ve been blessed to have a really good team.”
It’s actually the software that hints at where this gets interesting. Because while HEN is selling nozzles, it is accumulating something more valuable: data. Very specific, real-world data about how water behaves under pressure, how flow rates interact with materials, how fires react to suppression techniques, and how physics work in an active fire environment.
This is exactly what companies building the so-called world model need. These AI systems, which construct simulated representations of the physical environment to predict future states, require real multimodal data from physical systems under extreme conditions. Simulations alone cannot teach physics to AI. It is necessary for HEN to collect this for each deployment.
Sethi doesn’t elaborate, but he knows what he’s sitting on. Companies that train robotics and predictive physics engines will pay handsomely for this kind of real-world physics data.
Investors see it too. Last month, HEN closed a $20 million Series A round and received $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. This round brings the company’s total funding to more than $30 million.
Meanwhile, Sethi is already looking ahead. He said the company would resume fundraising in the second quarter of this year.
