This Founder Revolutionized Firefighting with AI Solutions

AI innovations enhance firefighting efficiency and safety

• High-efficiency nozzles aim to boost suppression rates (up to 300%) while conserving water (67%).
• A connected hardware-and-cloud platform turns “dumb” firefighting equipment into sensor-rich, GPS-enabled systems.
• The company is building a data pipeline and “data lake” to enable predictive analytics for emergency response.
• Traction has come despite slow government procurement cycles, with rapid revenue growth and a growing customer base.

The Genesis of HEN Technologies

HEN Technologies began with a deceptively simple premise: firefighting hardware—especially the humble nozzle—hasn’t changed much since the 1960s, even as fires have grown more complex and destructive. Sunny Sethi founded the company in June 2020 in Hayward, near California’s East Bay, naming it for “high-efficiency nozzles.” The initial focus was not software dashboards or AI, but the physics of how water actually suppresses fire under real conditions, including wind.

From the start, HEN’s approach was rooted in research and instrumentation. With funding from the National Science Foundation, Sethi pursued computational fluid dynamics work to understand how droplet size, velocity, and stream coherence affect suppression. The goal wasn’t merely to spray more water; it was to deliver water in a way that stays effective when conditions are working against firefighters.

That early emphasis on fundamentals shaped what HEN would become: a hardware company that behaves like a data company. The nozzle was conceived as the first “muscle on the ground,” but also as the first node in a broader system—one that could eventually measure, record, and optimize how water is deployed during active incidents.

By the time HEN started putting products into the market, the company’s ambition had expanded beyond a single piece of equipment. The nozzle was the entry point into a connected ecosystem designed to capture high-quality operational data—data that, in Sethi’s view, is a prerequisite for predictive analytics in emergency response.

Innovative Fire Suppression Technology

HEN’s core claim is bold: its nozzles can increase suppression rates by up to 300% while conserving 67% of water. Those numbers are striking in a field where incremental improvements are often the norm and where equipment standards can remain stable for decades. The company’s pitch is not that firefighters need more complexity, but that they need better control over the variables that matter most when seconds count.

At the center of HEN’s design philosophy is precision. Instead of treating water as a blunt instrument, HEN focuses on how water behaves as a stream—how it breaks into droplets, how it travels through air, and how it interacts with heat and wind. The company argues that controlling droplet size and velocity, and maintaining coherence in the stream, can translate into faster knockdown and less wasted water.

HEN has also framed its technology as a bridge between physical performance and digital intelligence. The nozzle is not just a mechanical endpoint; it’s part of a system that can be monitored and measured. That matters because firefighting often suffers from an information gap: crews may not have clear visibility into water usage, pressure requirements, or how changing conditions—especially wind—will affect suppression effectiveness.

The broader implication is that better suppression hardware can do more than improve outcomes at the nozzle tip. It can become a reliable source of operational data, enabling departments and incident commanders to understand what happened during a fire, how resources were used, and where bottlenecks or failures occurred.

How HEN Nozzles Work

HEN’s nozzle design is built around controlling the physics of the stream. According to Sethi, the nozzle precisely controls droplet size, manages velocity in new ways, and resists wind—three factors that can determine whether water reaches the seat of the fire effectively or disperses before it can do meaningful work.

In a comparison video HEN uses to demonstrate the difference, Sethi points to a key detail: the flow rate is the same. The distinction, he argues, is pattern and velocity control. In HEN’s depiction, the stream remains coherent, while a traditional nozzle’s stream disperses. The implication is that effectiveness isn’t simply a function of volume; it’s a function of delivery.

That emphasis on coherence matters in the real world because wind and turbulence can break up a stream, reducing the amount of water that actually lands where it’s needed. If a nozzle can maintain a more stable stream under the same flow rate, it can potentially improve suppression without demanding more water from hydrants, tenders, or onboard tanks.

HEN’s approach also aligns with a broader theme in the company’s strategy: turning firefighting into something measurable. A nozzle that behaves predictably and consistently is easier to model, easier to evaluate, and easier to integrate into a system that tracks performance across incidents.

Impact on Water Conservation

HEN says its nozzles conserve 67% of water, a claim that resonates far beyond cost savings. Water is a limiting factor in many incidents, and the consequences of running short can be severe. Sethi points to a recurring operational problem: fire departments can run out of water because there is often no communication between water suppliers and firefighters, and because multiple engines drawing from a single hydrant can create unpredictable pressure variations.

When two engines connect to one hydrant, pressure can fluctuate in ways that leave one engine suddenly getting nothing—even as a fire continues to grow. In rural areas, the challenge can be even more acute. Water tenders—tankers that shuttle water from distant sources—face logistical complexity that can quickly become a bottleneck if usage isn’t tracked and coordinated.

In that context, conserving water isn’t just environmentally appealing; it’s operationally strategic. Using less water for the same or better suppression outcome can reduce the risk of depletion, extend the effectiveness of limited supplies, and potentially ease coordination with utilities and water monitoring systems.

HEN’s broader platform is designed to quantify water use per incident: how much water was used, how it was used, which hydrant was tapped, and what the weather conditions were. Even before predictive analytics enters the picture, that level of visibility can help departments understand where water went—and how to avoid running out next time.

Sunny Sethi’s Background and Expertise

Sunny Sethi’s path to firefighting technology is not a straight line, and that may be part of the point. He describes his thinking as “bias free and flexible,” shaped by work across multiple industries and problem sets. Rather than coming up through traditional firefighting equipment channels, Sethi arrived with a materials and engineering background that had already been tested in demanding environments.

That cross-industry experience matters because firefighting is a domain where legacy approaches can persist for decades. A founder steeped only in the existing market might optimize within familiar constraints. Sethi’s background—spanning nanotechnology, solar, semiconductors, and automotive manufacturing—appears to have given him a different toolkit: one oriented toward surfaces, adhesion, materials processes, and the translation of research into manufacturable products.

It also helps explain why HEN’s story is not just about a better nozzle. The company’s trajectory suggests a founder comfortable moving from physical science to systems thinking: from droplet physics to connected devices, from hardware performance to cloud platforms, and from product sales to data pipelines.

Sethi is also candid about the limits of any one person’s expertise. He has said that if you ask him technical questions, he wouldn’t be able to answer everything—then credits the strength of his team. That admission is notable in a hardware-and-software company attempting to operate across mechanical engineering, electronics, cloud infrastructure, and government procurement.

Educational Journey

Sethi earned his PhD at the University of Akron, where he researched surfaces and adhesion. That focus—how materials interact at interfaces—may sound distant from firefighting at first glance, but it sits at the heart of many applied engineering problems. Fire suppression is ultimately about interactions: water droplets meeting heat, surfaces, air currents, and combustion dynamics.

A doctoral background also signals something else: comfort with rigorous experimentation and the patience required to iterate toward a result. HEN’s early work, supported by National Science Foundation funding, relied on computational fluid dynamics research to analyze how water suppresses fire and how wind affects it. That kind of modeling-heavy approach fits naturally with a founder trained in research.

The throughline from surfaces and adhesion to firefighting is not literal; it’s methodological. It’s the habit of breaking down complex physical phenomena into variables that can be studied, modeled, and engineered. In HEN’s case, those variables include droplet size, velocity, and stream coherence—parameters that can be tuned, tested, and compared.

Previous Ventures and Experience

Before HEN, Sethi founded ADAP Nanotech, which developed a carbon nanotube-based portfolio and won grants from the Air Force Research Lab. That experience placed him in an ecosystem where advanced materials meet real-world performance requirements—often under strict evaluation.

He later worked at SunPower, developing new materials and processes for shingled photovoltaic modules, and then at TE Connectivity, where he worked on devices using new adhesive formulations to enable faster manufacturing in the automotive industry. Across these roles, the recurring theme is applied innovation: not just inventing, but making something manufacturable and scalable.

Those experiences likely shaped how HEN approached a conservative market. Firefighting equipment must be reliable, durable, and trusted by end users whose lives depend on it. At the same time, departments often buy through government procurement cycles that can be slow and exacting. A founder who has navigated industrial processes and performance-driven environments may be better prepared for that combination of technical and operational constraints.

Sethi’s career also suggests a comfort with moving between domains—an ability that becomes critical when a company tries to fuse hardware, embedded computing, and cloud software into a single platform.

Inspiration Behind HEN Technologies

The spark for HEN was personal, and it arrived in waves—much like the fire seasons that reshaped Northern California in the late 2010s. After moving from Ohio to the East Bay outside San Francisco in 2013, Sethi and his family experienced a sequence of major fires: the Thomas Fire, the Camp Fire, and the Napa-Sonoma fires. What initially felt like an extraordinary event became a pattern.

The breaking point came in 2019. Sethi was traveling during evacuation warnings while his wife was home alone with their three-year-old daughter, with no family nearby, facing the possibility of an evacuation order. Sethi recalls his wife’s anger in blunt terms: “Dude, you need to fix this, otherwise you’re not a real scientist.”

That challenge reframed the problem. Instead of viewing wildfires as an external threat to endure, Sethi began to see them as an engineering problem he might be able to influence. His background across multiple industries had already taught him that entrenched systems can change—sometimes quickly—when someone brings a different perspective and a willingness to question assumptions.

Inspiration, in this case, wasn’t abstract. It was rooted in the anxiety of evacuation warnings and the practical reality that families and communities were being asked to live with recurring fire risk. It also carried an implicit critique: if a scientist can work on advanced materials for solar modules or adhesives for automotive manufacturing, why shouldn’t that same rigor be applied to firefighting tools that have remained largely unchanged for decades?

HEN’s origin story is therefore not just about invention; it’s about urgency. The company’s early focus on suppression efficiency and water conservation reflects a desire to improve outcomes on the ground. But the later expansion into connected systems suggests that Sethi’s ambition grew: not only to fight fires better, but to make firefighting more measurable, more predictable, and ultimately more intelligent.

Research and Development at HEN

HEN’s R&D story begins with computational fluid dynamics and expands into a broader pattern: engineering hardware that can generate high-quality data. The company’s early work, supported by National Science Foundation funding, focused on understanding how water suppresses fire and how wind affects suppression. That research produced a nozzle designed to control droplet size precisely, manage velocity differently, and resist wind.

But R&D at HEN did not stop at the nozzle. As the company expanded into monitors, valves, overhead sprinklers, and pressure devices, it also embedded sensors and computing power into its products. Sethi has said that each device contains custom-designed circuit boards—23 different designs—turning traditional equipment into smart, connected hardware. Some of these devices are powered by Nvidia Orion Nano processors.

This combination—mechanical design plus embedded electronics—sets up the company’s longer-term strategy. Predictive analytics and AI require data, and data quality depends on instrumentation. HEN’s view is that you can’t build predictive systems for emergency response without good quality data, and you can’t get good quality data without the right hardware.

The company’s patent activity underscores how much of its differentiation it believes lies in engineering. HEN has filed 20 patent applications, with half a dozen granted so far. That portfolio suggests ongoing innovation not only in nozzle performance but in the broader system of connected devices and controls.

Computational Fluid Dynamics Research

HEN’s early computational fluid dynamics work was aimed at a practical question: how does water actually suppress fire under varying conditions, and how does wind change the equation? Rather than treating suppression as a simple matter of flow rate, the research examined the behavior of water as it travels through air and interacts with fire dynamics.

The output of that work was a nozzle designed to control droplet size precisely and manage velocity in new ways, with an emphasis on resisting wind. In other words, the nozzle is engineered not just to deliver water, but to deliver it effectively when conditions are hostile.

Sethi’s demonstration of HEN’s comparison video reinforces the research-driven framing. The claim is not that HEN uses more water; it’s that, at the same flow rate, HEN’s pattern and velocity control keep the stream coherent while traditional nozzles disperse. That coherence is presented as a key mechanism behind improved suppression.

Computational modeling also fits HEN’s broader ambition to quantify firefighting. If the company can model how water behaves and then instrument devices to measure real-world performance, it can begin to close the loop between theory and practice—an essential step if the end goal is predictive analytics.

Patent Applications and Innovations

HEN has filed 20 patent applications, with half a dozen granted so far, according to Sethi. While the company has not publicly detailed every claim in that portfolio in the information available here, the scale of filings signals a deliberate effort to protect its approach across hardware performance, embedded intelligence, and system-level integration.

The patent activity also aligns with the company’s rapid expansion beyond nozzles. HEN now sells not only nozzles but also monitors, valves, overhead sprinklers, and pressure devices, and it is launching additional flow-control and discharge control systems. Each of these products can be a site of innovation—especially when combined with custom circuit boards, sensors, and onboard computing.

What makes this notable in the firefighting market is the combination of physical and digital defensibility. Traditional equipment makers may compete on durability, brand, and distribution. HEN is attempting to compete on physics, instrumentation, and data architecture—areas where patents can matter, particularly if the company’s long-term value is tied to the uniqueness of the data it can collect and the systems it can build on top of it.

In that sense, the patents are not just about protecting a better nozzle. They are part of building a platform—one that starts with hardware but points toward software intelligence and, eventually, AI-driven applications.

Expansion of HEN’s Product Line

HEN’s product roadmap has moved quickly from a single breakthrough component to a broader suite of connected firefighting equipment. The nozzle may be the company’s headline product, but Sethi has described it as only the beginning—the “muscle on the ground.” The larger strategy is to place smart, sensor-equipped devices throughout the firefighting system so that water usage, pressure, location, and conditions can be tracked in real time.

To that end, HEN has expanded into monitors, valves, overhead sprinklers, and pressure devices. It is also launching a flow-control device called “Stream IQ” and discharge control systems this year. The common thread is not just mechanical function; it’s embedded intelligence. Sethi says each device contains custom-designed circuit boards with sensors and computing power, with 23 different designs across the product line. Some devices use Nvidia Orion Nano processors.

This expansion matters because it increases the number of “data nodes” in the field. HEN is not monetizing the data yet, but it is implementing these nodes, putting devices into as many systems as possible, and building the data pipeline and data lake. The more comprehensive the hardware footprint, the more complete the operational picture becomes—especially when devices can be linked to pump-level sensing and cloud applications.

The product line expansion also reflects a pragmatic understanding of how firefighting works. Nozzles alone don’t solve coordination problems between engines, hydrants, and water suppliers. A system that spans pumps, flow control, discharge control, and location-aware devices is better positioned to address the resource allocation and communication gaps that can cause departments to run out of water mid-incident.

Upcoming Products: Stream IQ

Among HEN’s upcoming products is a flow-control device called “Stream IQ,” which the company is launching this year, alongside discharge control systems. While detailed specifications are not provided here, the naming and placement in the lineup suggest a focus on controlling and measuring how water is delivered—an extension of the nozzle’s emphasis on precision.

Flow control is not a minor feature in firefighting. Water supply can be volatile, especially when multiple engines draw from a single hydrant or when rural operations depend on tenders shuttling water from distant sources. In those scenarios, knowing how much water is flowing, at what pressure, and for how long can be the difference between stable operations and sudden failure.

Stream IQ also fits HEN’s broader architecture: sensors at the pump can act as a “virtual sensor” in the nozzle, tracking when it’s on, how much water flows, and what pressure is required. A flow-control device can strengthen that chain of measurement and control, potentially improving both performance and data quality.

Just as importantly, new products like Stream IQ expand HEN’s presence in the field. Each additional device is another opportunity to capture incident-level data—how water was used for a given fire, under what weather conditions, and with what resource constraints. That data, in turn, is what HEN believes will enable the next layer of value: intelligence in the cloud.

Integration of Smart Technology

HEN’s expansion is inseparable from its integration of smart technology. Sethi says each device contains custom-designed circuit boards with sensors and computing power—23 different designs that turn traditional hardware into connected equipment. Some of these devices are powered by Nvidia Orion Nano processors, underscoring that HEN is not merely adding basic telemetry; it is building for on-device computation as well as cloud connectivity.

The system-level design is central: sensors at the pump act as a virtual sensor in the nozzle, tracking exactly when it’s on, how much water flows, and what pressure is required. From there, the platform can capture a detailed record of an incident: how much water was used, how it was used, which hydrant was tapped, and what the weather conditions were.

HEN’s cloud platform includes application layers that Sethi likens to what Adobe did with cloud infrastructure—suggesting modular tools tailored to different roles, such as fire captains, battalion chiefs, and incident commanders. The system includes weather data and GPS in all devices, enabling alerts such as wind shift warnings or notifications that a particular fire truck is running out of water.

This integration is not framed as technology for technology’s sake. It is positioned as a response to real operational failures—like the lack of communication between water suppliers and firefighters, and the unpredictable pressure dynamics when multiple engines share a hydrant. Smart hardware becomes the foundation for smarter decisions.

HEN Technologies’ Market Impact

HEN’s impact is best understood as a two-front campaign: selling hardware into a conservative, procurement-heavy market while quietly building a data asset that could reshape what firefighting technology means. On the commercial side, the company has demonstrated rapid growth since launching its first products in the second quarter of 2023. On the strategic side, it is positioning itself as a platform company—one that can support predictive analytics and, eventually, AI applications.

The traction is notable because firefighting is not an easy market to penetrate. Sethi describes it as a “B2C play” in terms of convincing end users to buy, but with a “B2B” procurement cycle because government purchasing processes ultimately control budgets and approvals. HEN claims it has “cracked both,” building products that resonate with firefighters while navigating the slow machinery of public-sector buying.

The company’s customer footprint has expanded quickly. It 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 the U.S. General Services Administration (GSA) after a year-long vetting process, a federal seal of approval that can make it easier for military and government agencies to buy.

Competition exists across both hardware and software. IDEX Corp sells hoses, nozzles, and monitors. Software companies like Central Square serve fire departments. First Due, a Miami company selling software to public safety agencies, announced a $355 million round last August. Still, Sethi argues that no company is doing exactly what HEN is trying to do—particularly the integration of smart hardware, cloud applications, and data capture designed for predictive analytics.

Revenue Growth and Customer Base

HEN’s revenue trajectory, as described by Sethi, shows a steep climb from early pilots to broader adoption. The company launched its first products into the market in the second quarter of 2023, lining up 10 fire departments and generating $200,000 in revenue. In 2024, revenue reached $1.6 million. Last year, it hit $5.2 million. This year, HEN is projecting $20 million in revenue.

Customer growth has followed a similar pattern. HEN currently has 1,500 fire department customers. It also serves high-profile and demanding clients, including the Marine Corps, US Army bases, Naval atomic labs, NASA, and Abu Dhabi Civil Defense, and it ships to 22 countries. That breadth suggests the products are not confined to a single niche or geography.

Distribution has been a key lever. HEN works through 120 distributors, a practical necessity in a market where relationships, service, and procurement pathways matter. The company also recently qualified for GSA after a year-long vetting process, which can streamline purchasing for federal agencies and the military.

Sethi argues that the constraint is not demand but scaling fast enough. In a market where departments buy about 20,000 new engines each year to replace aging equipment in a national fleet of 200,000, qualification and standardization can translate into recurring opportunities. HEN’s bet is that once its hardware is embedded, the data-driven layer can generate value between purchase cycles.

Challenges in the Firefighting Market

HEN’s growth has come despite structural challenges that can stall even strong products. Sethi describes the market as uniquely difficult because it requires winning over end users—firefighters who must trust equipment in life-or-death situations—while also navigating government procurement cycles that function more like enterprise sales.

That duality shapes everything from product design to go-to-market strategy. A product can’t just satisfy a purchasing checklist; it has to “resonate” with the people who will hold it, aim it, and rely on it under pressure. At the same time, even enthusiastic end users can be constrained by budget cycles, approvals, and compliance requirements.

Scaling is another challenge. HEN’s footprint spans 1,500 fire department customers, multiple branches of the U.S. military, and international shipments to 22 countries. Meeting that demand requires manufacturing capacity, distribution coordination, and support—especially as products become more complex with sensors, custom circuit boards, and computing components.

The competitive landscape adds pressure. Established hardware players like IDEX Corp already sell core equipment such as hoses, nozzles, and monitors. On the software side, companies like Central Square and First Due serve public safety agencies. HEN’s differentiation rests on being neither purely hardware nor purely software, but a tightly integrated system that can generate the data needed for predictive analytics. The challenge is convincing a risk-averse market to adopt a new category rather than a familiar vendor.

Future Prospects and Data Utilization

HEN’s most ambitious bet is that the real value of its business will extend beyond hardware sales into data-driven intelligence. The company is already capturing detailed operational information: when a nozzle is on, how much water flows, what pressure is required, which hydrant was tapped, and what weather conditions were present. Devices include GPS, and the platform integrates weather data, enabling real-time warnings such as wind shifts or low-water alerts.

For now, HEN is not monetizing that data. Sethi says the company is implementing data nodes, putting devices in as many systems as possible, building the data pipeline, and creating the data lake. The plan is to start commercializing the application layer—with built-in intelligence—next year.

This direction aligns with what the U.S. Department of Homeland Security has been asking for through its NERIS program, an initiative aimed at bringing predictive analytics to emergency operations. Sethi’s framing is blunt: predictive analytics require good quality data, and good quality data requires the right hardware. HEN is attempting to supply both.

Beyond emergency response, the data HEN collects may have value in adjacent AI domains. The company is accumulating real-world, multimodal data about how water behaves under pressure and how suppression interacts with active fire environments—exactly the kind of data that can be difficult to obtain and that could be valuable to companies building “world models” and predictive physics engines. Sethi has not elaborated publicly, but he appears aware of the strategic asset he is building.

Predictive Analytics in Emergency Response

HEN’s platform is designed to close a persistent information gap in firefighting: the lack of real-time, shared visibility into water usage and resource constraints. Sethi points to incidents where departments ran out of water because there was no communication between water suppliers and firefighters, and because pressure dynamics can become unpredictable when multiple engines draw from a single hydrant.

By placing sensors at the pump and treating them as a virtual sensor in the nozzle, HEN can track when water is flowing, how much is being used, and what pressure is required. Combined with GPS and weather data, the system can provide operational alerts—such as warning crews that wind is about to shift and they should move engines, or that a particular truck is running low on water.

This is the foundation for predictive analytics: not just recording what happened, but anticipating what will happen next. DHS’s NERIS program is explicitly aimed at predictive analytics for emergency operations, and HEN’s approach is to build the data infrastructure required to make those predictions credible.

The emphasis on data quality is central. In emergency response, bad data can be worse than no data, because it can create false confidence. HEN’s strategy is to instrument the physical system—pumps, nozzles, flow control, discharge control—so that the data reflects real conditions, not estimates or manual logs.

Potential for AI Applications

HEN’s longer-term AI potential rests on the uniqueness of the data it can collect. While many AI systems can be trained on simulations, Sethi’s story highlights a limitation: you can’t teach AI about physics through simulations alone. Systems that aim to model physical environments—so-called world models—require real-world, multimodal data, especially from extreme conditions that are hard to replicate.

HEN is collecting precisely that kind of data with every deployment: how water behaves under pressure, how flow rates interact with materials, how fire responds to suppression techniques, and how physics plays out in active fire environments. This is not generic sensor data; it is operational data generated during real incidents and real training scenarios, tied to equipment performance and environmental conditions.

Sethi has not said HEN will sell this data, and the company is not monetizing it yet. But the strategic implication is clear: companies training robotics systems or predictive physics engines could find such data highly valuable, because it is difficult to obtain at scale and under consistent instrumentation.

Investors appear to recognize the upside. HEN closed a $20 million Series A round last month, 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, bringing total funding to more than $30 million. Sethi has said the company expects to return to fundraising in the second quarter of this year—suggesting that the next phase, likely centered on scaling and software commercialization, will require additional capital.

Innovative Approaches in Firefighting Technology

The Evolution of Fire Suppression Systems

HEN’s story illustrates how firefighting technology may be entering a new phase—one where performance improvements in hardware are inseparable from measurement and connectivity. For decades, much of the market has been defined by durable equipment and incremental refinements. Sethi’s claim that the industry has remained largely unchanged since the 1960s is less an insult than a description of how hard it is to innovate in a safety-critical domain.

What HEN is attempting is a layered evolution. The first layer is mechanical: a nozzle engineered to control droplet size, manage velocity, and resist wind, with claimed gains in suppression rate and water conservation. The second layer is electronic: custom circuit boards, sensors, and onboard computing embedded across devices, turning equipment into a network of data nodes. The third layer is software: a cloud platform with application layers tailored to roles in the field, integrating GPS and weather data to provide actionable alerts.

This evolution matters because it reframes what “fire suppression equipment” can be. Instead of isolated tools, devices become part of a system that can be evaluated, compared, and improved over time. It also creates a feedback loop: better hardware generates better data; better data enables better decision-making; better decisions inform the next generation of hardware and software.

HEN is not alone in serving the market—hardware incumbents and software vendors are well established—but its integrated approach suggests a shift in the category itself. The question is no longer only which nozzle sprays best, but which system helps departments understand and manage suppression as a coordinated, data-informed operation.

Harnessing Data for Enhanced Emergency Response

The most consequential change HEN is pushing is cultural as much as technical: treating firefighting as a data problem without losing sight of the realities on the ground. The company’s platform captures incident-specific details—water usage, hydrant selection, pressure requirements, weather conditions—and makes them available through cloud applications designed for different command roles.

That capability directly addresses operational failures that can escalate incidents, such as running out of water due to poor coordination with water suppliers or unpredictable pressure drops when multiple engines share a hydrant. In rural settings, where tenders shuttle water from distant sources, the ability to integrate water usage calculations with utility monitoring systems could help optimize resource allocation.

HEN’s approach also aligns with broader institutional interest. DHS’s NERIS program is seeking predictive analytics for emergency operations, but predictive systems depend on high-quality data. HEN’s argument is that the path to prediction starts with instrumentation: sensors, connected devices, and reliable measurement at the point of action.

For now, HEN is building the foundation—data nodes, pipelines, and a data lake—before monetizing intelligence. If the company succeeds, the payoff could be twofold: more efficient suppression today, and a future where emergency response decisions are supported by predictive insights grounded in real-world physics data collected at scale.