We’re excited to announce Distributed Spectrum’s $25M Series A—an oversubscribed round led by Conviction, Shield Capital, and Nat Friedman with participation from existing investors, Felicis and XFund, along with angels including leaders in technology, defense, and AI (Stan McChrystal, Eric Glyman, Chris Re, Arash Ferdowsi, Matt MacInnis, Zak Stone, and executives from Palantir).

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A few months ago, we were a team of just seven engineers. With that team, we were able to close over $7M in contracts in a span of just 60 days across the US Department of Defense. Since then we’ve more than doubled our team, made our first hires in product and operations, moved to a new office in NYC—and we're just getting started.

Our focus is on building software and sensors to let anyone identify critical radio signals across defense missions. This domain, called electronic warfare, has rapidly become one of the most important in today’s combat operations due to the evolution of the modern battlefield.

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The war in Ukraine is the first conflict truly centered around 21st century technology. For the first time, there is a proliferation of unmanned systems, each of which relies on radio signals to communicate and operate. The modern battlefield is now choked with signals; drones, cell phones, handheld radios, satellite uplinks, GPS, and so much more, all relying on radio. Soldiers on the front lines are forced to use hobbyist lab equipment to look at raw waveforms to map nearby drones and jammers. The ability to locate and jam your adversary has made radio as important to military outcomes as terrain or weather.

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This is why Russia and China are investing billions of dollars in developing novel electronic warfare technology to autonomously understand and manipulate radio signals at scale. Meanwhile, the US largely relies on decades-old hardware that is extremely expensive and requires co-located, trained experts to manually configure and parse complex raw outputs.

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Not only do these systems not work on a congested battlefield like in Ukraine, but they cannot scale to the vast reaches of the Pacific Ocean and the challenges faced in deterring and prevailing in a future fight. The logistics and infrastructure required, simply put, cannot exist. We cannot place large numbers of million-dollar sensors across the ocean and constantly deploy experts to operate them.  We need tools to sense and make sense of all aspects of the environment, both in daily competition and if conflict arises.

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Radio signals are everywhere so we need sensors everywhere. To be effective, those sensors need to be able to operate locally with the knowledge of a signals expert. The visual domain is leaps and bounds ahead–we can put cheap cameras everywhere and use a computer vision model to alert humans when something interesting happens. We now need a similar solution to effectively monitor the wireless world at scale.

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The success of every mission today and going forward relies on the radio spectrum. Automated tools that help us understand it make the trained experts we do have 1000x more efficient, and make it possible to bring this intelligence to places where experts can’t go.

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The first products we’ve deployed do exactly this: pair our own foundational machine learning models with inexpensive hardware to bring radio intelligence to any platform. Our capabilities are already being used in Ukraine to help those on the front lines identify threats, and we’re working actively with the nation’s most elite units to help change the way we operate in the electromagnetic spectrum.

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When we graduated from Harvard in 2022 and moved to New York City to build out Distributed Spectrum’s engineering team, we had a clear technical vision and compelling prototypes but practically no experience selling to the government. Getting to our first successful deployments with customers required a deep coupling between our engineering efforts and our end users, the men and women in uniform who experience the problems we are trying to solve on a daily basis.

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Building cutting-edge machine learning capabilities for resource-constrained platforms is technically engaging, but actually watching the impact it has on our customers remains our favorite part of our jobs as founders. Over time we have grown our base of customers to cover an extremely diverse set of missions: ranging from providing real-time alerts of enemy activity with a sensor that can be placed in an operator’s backpack to building low-cost payloads that customers can easily strap to FPV drones in Ukraine.

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Initially, we were met with a lot of skepticism around how useful our system or really any AI-enabled system could be at solving problems that usually require years of technical specialization. Today, the concept of applying artificial intelligence to solve spectrum challenges is no longer controversial. Every DoD service is gearing up to spend billions of dollars completely overhauling how they fight in the radio spectrum, with an emphasis on large numbers of software-defined sensors bringing spectrum intelligence to every warfighter. 

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We’re extremely proud of the trust and demonstrated value we’ve been able to achieve with our first customers. Now that we have a validated capability and strong end-user advocates, we’re excited for Distributed Spectrum’s next chapter as we grow our team and build our capacity to deliver our products at scale.