Tech Explained: Here’s a simplified explanation of the latest technology update around Tech Explained: HEN Technologies raises $22M to turn firefighting into AI play in Simple Termsand what it means for users..
Sunny Sethi’s smart nozzle startup is building the data layer for predictive emergency response
PUBLISHED: Sun, Jan 25, 2026, 11:39 PM UTC | UPDATED: Mon, Jan 26, 2026, 12:49 AM UTC
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HEN Technologies raised $22 million in Series A funding led by O’Neil Strategic Capital, with participation from NSFO, Tanas Capital, and z21 Ventures, plus $2 million in venture debt from Silicon Valley Bank
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The company’s smart firefighting equipment is deployed across 1,500 fire departments, generating real-world physics data from extreme conditions that AI world models desperately need
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Revenue jumped from $200,000 in Q2 2023 to a projected $20 million in 2026, with customers including the Marine Corps, NASA, and fire departments in 22 countries
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HEN plans to commercialize its predictive analytics platform in 2027 and is already preparing for another funding round in Q2 2026
Sunny Sethi didn’t set out to build an AI company when he started designing better fire nozzles in 2020. But the founder of HEN Technologies just closed a $22 million funding round for something far more valuable than hardware – a real-world physics data platform that could reshape how AI systems understand the physical world. What started as a solution to California’s wildfire crisis has quietly evolved into a data play that has investors betting big on the intersection of emergency response and machine learning.
HEN Technologies founder Sunny Sethi sounds almost casual when describing how his company increased fire suppression rates by up to 300% while cutting water usage by 67%. It’s the kind of breakthrough that would make most founders lean into the pitch, but Sethi is already three steps ahead, focused on what he calls “the muscle on the ground” – and the data goldmine it’s creating.
The origin story reads like a pivot born from personal crisis. After earning his PhD at the University of Akron and bouncing through roles at ADAP Nanotech, SunPower, and TE Connectivity, Sethi moved his family from Ohio to California’s East Bay in 2013. Then came the megafires – Thomas, Camp, Napa-Sonoma – each one closer, each one more terrifying. In 2019, while Sethi was traveling, his wife faced potential evacuation alone with their three-year-old daughter. Her ultimatum was blunt: “Dude, you need to fix this, otherwise you’re not a real scientist.”
That challenge launched HEN Technologies in June 2020. With National Science Foundation funding, Sethi dove into computational fluid dynamics research, analyzing how water suppresses fire and how wind disrupts traditional nozzles. The result was hardware that controls droplet size with precision, manages velocity in ways legacy equipment can’t, and resists wind interference. In side-by-side comparisons, HEN’s nozzles maintain coherent streams while traditional systems disperse – same flow rate, radically different outcomes.
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But the nozzle was never the endgame. HEN has since expanded into monitors, valves, overhead sprinklers, and pressure devices, launching its “Stream IQ” flow-control device and discharge control systems this year. Each piece of equipment contains custom-designed circuit boards with sensors and computing power – 23 different designs in total, some powered by Nvidia Orion Nano processors. The company has filed 20 patent applications with half a dozen granted so far, according to TechCrunch.
What HEN is really building is a connected system that captures granular data about every deployment. Sensors at the pump act as virtual sensors in the nozzle, tracking when equipment is active, how much water flows, what pressure is required, which hydrant is tapped, and what weather conditions exist. It’s the kind of infrastructure the Department of Homeland Security has been requesting through its NERIS program, which aims to bring predictive analytics to emergency operations. “But you can’t have [predictive analytics] unless you have good quality data,” Sethi told TechCrunch. “You can’t have good quality data unless you have the right hardware.”
The data problem is urgent. Fire departments routinely run out of water because there’s no communication between water suppliers and firefighters on the ground. It happened during the Palisades Fire. It happened during the Oakland Fire decades earlier. When two engines connect to one hydrant, pressure variations can leave one truck suddenly dry as fires intensify. In rural areas, water tenders shuttling from distant sources face logistical chaos without real-time resource tracking.
HEN’s cloud platform addresses this with application layers tailored for fire captains, battalion chiefs, and incident commanders – what Sethi compares to Adobe’s cloud infrastructure model. The system integrates weather data and GPS across all devices, warning front-line crews when wind is about to shift or when a particular truck is running low on water. Next year, HEN plans to start commercializing this application layer with built-in intelligence.
The traction is remarkable for hardware sold into notoriously slow government procurement cycles. “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,” Sethi explained. “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 tell the story. HEN launched its first products in Q2 2023, signing 10 fire departments and generating $200,000 in revenue. Word spread fast. Revenue hit $1.6 million in 2024, then $5.2 million in 2025. This year, with 1,500 fire department customers, HEN is projecting $20 million in revenue. The company now serves the Marine Corps, US Army bases, Naval atomic labs, NASA, Abu Dhabi Civil Defense, and ships to 22 countries through 120 distributors. It recently qualified for GSA after a year-long vetting process, unlocking easier procurement for military and government agencies.
Competition exists – IDEX Corp sells hoses and nozzles, Central Square provides software to fire departments, and Miami-based First Due raised a massive $355 million round last August. But “no company is doing exactly what we are trying to do,” Sethi insists, and investors seem to agree.
Last month, HEN closed a $20 million Series A led by O’Neil Strategic Capital, with NSFO, Tanas Capital, and z21 Ventures participating, plus $2 million in venture debt from Silicon Valley Bank. The round brought total funding to over $30 million.
But here’s where the story pivots from firefighting to AI. While HEN sells nozzles and monitors, it’s quietly amassing something far more valuable: 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 world models need – AI systems that construct simulated representations of physical environments to predict future states. These systems require real-world, multimodal data from physical systems under extreme conditions. You can’t teach AI about physics through simulations alone.
Sethi won’t elaborate on plans to monetize this data, but he knows what he’s sitting on. Companies training robotics and predictive physics engines would pay handsomely for the kind of real-world physics data HEN collects with every deployment. It’s the classic hardware-as-a-wedge-for-data play, except HEN’s data comes from environments no lab can replicate.
To execute on both hardware and software, HEN has built a team that bridges both worlds. Its software lead was formerly a senior director who helped build Adobe’s cloud infrastructure. The 50-person team includes 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, “but I have such good teams that [it] has been a blessing.”
The hardware provides recurring revenue – fire departments buy about 20,000 new engines annually to replace aging equipment in a national fleet of 200,000. Once HEN is qualified, it becomes recurring revenue, and because the hardware generates data, revenue continues between purchase cycles. The constraint isn’t demand, Sethi says. It’s scaling fast enough.
Sethi is already looking ahead. He says the company will return to fundraising in the second quarter of this year, likely to accelerate deployment and data collection before competitors realize what game HEN is really playing.
What looks like a firefighting hardware company is quietly building the infrastructure for predictive emergency response – and potentially a data layer that AI companies will need as they move from simulated environments to real-world physics. Sethi’s bet is that the nozzles are just the wedge, and the real value is in the data they generate from environments no one else can access. With 1,500 departments deployed and revenue scaling fast, HEN is positioning itself at the intersection of emergency response, IoT hardware, and AI training data. The next funding round will reveal whether investors are buying firefighting equipment or the future of physical AI. Either way, Sethi has already moved past the nozzles.