Editor’s Brief¹

Last week, we looked at Epirus and how high-power microwaves are reshaping layered defense against drone swarms. Consider this: it took 73 C-17 loads to move a single Patriot battalion from the Pacific to the Middle East. (source)

Next week, we’ll go deeper into this massive logistics problem—because no matter how great the tech, it still has to get into theater.

This week, we turn to the electromagnetic spectrum.

As adversaries field faster, more adaptive signals, a sharper question is emerging:
How do you see, track, and respond before the threat evolves again?

Distributed Spectrum is one of the companies pushing toward that answer.

Signal Brief: Distributed Spectrum — Small Sensors Powering the New Kill Web

Distributed Spectrum is an early-stage startup pioneering AI-powered radio frequency (RF) sensing and signals intelligence (SIGINT) solutions. Their flagship product—a network of small, ruggedized RF sensors driven by edge AI—addresses the critical lack of persistent spectrum awareness at the tactical level.

Origins & Vision

Distributed Spectrum was founded in 2020 by Alex Wulff, Isaac Struhl, and Ben Harpe. What began as Wulff’s Harvard undergraduate thesis idea quickly evolved into a startup during a COVID-19 gap year. Their early prototype demonstrated that sophisticated RF signal detection could be achieved without high-end military hardware.

Initially exploring commercial applications, the team pivoted after winning a National Security Innovation Network (NSIN) hackathon in early 2021, where firsthand accounts from military operators highlighted urgent gaps in RF situational awareness.

By late 2024, Distributed Spectrum closed over $7 million in contracts within a 60-day span. These wins set the stage for a $25 million Series A financing round announced in March 2025, positioning the company as one of the top emerging players in defense AI.

Distributed Spectrum’s mission is to “build software and sensors that let anyone understand critical radio signals in any mission.” In practice, this means empowering users to detect and interpret important RF signals without requiring expensive equipment or specialized training.

Key Takeaways

• Edge AI-Enabled Threat Detection — On-device processing allows frontline units to act without relying on connectivity or off-site analysts.

• Mesh-Based Geolocation — Each sensor contributes to a distributed network, enabling triangulation of signal emitters through time-synchronized detection.

• Attritable, Scalable Hardware — Consumer-grade components plus custom machine learning models enable low-cost, high-volume deployments.

• Ukrainian Validation — Sensors have reportedly been deployed with Ukrainian forces to identify enemy drone controllers and jamming devices in real time.

• Investor Confidence & Traction — Over $7 million in DoD and IC contracts secured, followed by a $25 million Series A led by Shield Capital and Conviction.

Tech Radar:

AI signals expert” in a box

Distributed Spectrum’s platform is a mesh of small, inexpensive RF sensors designed to detect, classify, and localize RF signals—such as communications, jamming, or drone control emissions—without human intervention.

Key Capabilities

• Low SWaP-C Design — Each sensor is roughly the size of a thin stack of cocktail napkins and contains $1,500–$2,000 worth of commercial hardware.

• Autonomous Signal Classification — Custom machine learning models optimized for low-power, edge environments.

• Distributed Geolocation — Sensor triangulation accuracy improves as more units are deployed.

• Platform Agnostic — Sensors can be mounted on vehicles, drones, or used as standalone ground nodes.

• Instant Alerts — A simple UI delivers real-time warnings to non-specialist users.

By developing specialized AI models optimized for constrained computing environments, Distributed Spectrum has solved the problem of accurately classifying complex signals without massive servers or expert operators. Their portfolio of 14 patents (6 granted, 8 pending) on distributed RF signal processing underscores the sophistication of their approach

Market Signals

Funding & Growth

• Total Funding: $29M across early stage and Series A rounds

• Latest Round: $25M Series A (March 2025) led by Conviction and Shield Capital

• Notable Investors: Conviction Capital, Shield Capital, Nat Friedman (former GitHub CEO), Felicis Ventures, XFund, Chris Re (Stanford AI Professor), General Stanley McChrystal

• Valuation: Undisclosed

• Contract Growth: $50K in innovation prizes (2021) → $7M+ in DoD/IC contracts (2024-25)

Contracts & Government Traction²

Distributed Spectrum’s major contract wins include:

• SBIR Phase 2 (Air Force Research Labs, April 2024): $1.248M ceiling through June 2025 to develop low-SWaP RF situational awareness tools.

• SBIR Phase 1 (AFRL, May 2024): Focused on automating adversary RF collection and localization using attritable sensors.

• AUKUS EW Challenge Winner: Secured a $150K prize, opening future international opportunities.

• Army Research Office (September 2024): Integration of distributed RF sensing into strategic strike and multi-domain operations frameworks.

• Washington Headquarters Services OTA (December 2024): $1.88M for classified R&D; potential total contract value of $7.85M.

Distributed Spectrum’s sensors have seen operational use under live-fire conditions, detecting adversarial jammers and drone control signals in Ukraine. The company’s rapid contract ramp highlights its agility navigating defense procurement channels.

Looking Ahead

Electronic warfare (EW) is not a new domain, though it often receives less attention than land, sea, air, or space. 

In 1904, the British cruiser HMS Diana intercepted a wartime radio transmission, revealing Russian fleet movements and reshaping the Russo-Japanese War. By the Gulf War, GPS demonstrated both its battlefield utility and its vulnerability to simple jamming techniques.

Today, the electromagnetic (EM) spectrum is as contested as any other domain.

Ukrainian forces, working alongside startups, have rapidly adapted to Russian EW threats by fielding small RF nodes, mobile jammers, and real-time signal analysis tools. Russia, in turn, has restored and advanced its capabilities, dynamically jamming drones, spoofing GPS, and disrupting frontline communications.

Distributed Spectrum’s success in Ukraine offers a glimpse of how future EW operations must evolve. But the Indo-Pacific presents even greater challenges.

At the forefront is China’s rapidly advancing RF and radar ecosystem. New systems like Synthetic Impulse and Aperture Radar (SIAR) are designed to detect stealth aircraft, while fire control radars supporting HQ-9 and YJ-18 missile systems now feature frequency agility and low-probability-of-intercept (LPI) modes, making them harder to jam and more trusted in dynamic engagements.

Meanwhile, Over-the-Horizon Radars (OTHR) extend China’s surveillance reach thousands of kilometers beyond its coastline. Unlike conventional radars constrained by the curvature of the Earth, OTHR systems exploit skywave propagation, allowing China to monitor U.S. carrier groups, missile launches, and air movements at strategic distances—threatening to outpace traditional U.S. kill chains.³

Distributed Spectrum co-founder Alex Wulff put it plainly:

Before any kinetic operations begin, land-based assets—alongside wideband surveillance platforms like the RC-135V/W Rivet Joint and E-2D Advanced Hawkeye—could integrate Distributed Spectrum’s sensors into daily patrols, creating a persistent SIGINT force and automating detection tasks. Instead of waiting weeks or months to update threat libraries, a distributed sensor network could enable near-real-time identification of new emitter signatures and tactics.

Thanks to their small size and low power requirements, these modular nodes could even be covertly seeded deep inside sensitive areas of the Indo-Pacific, enhancing situational awareness and closing critical gaps in the electromagnetic picture.

In an Indo-Pacific conflict where speed and adaptability will decide the electromagnetic fight, Distributed Spectrum’s approach could shift the balance of awareness and control back toward U.S. and allied forces.

Challenges

• Classification Accuracy — Reducing false positives in dense, contested, and dynamic RF environments without overwhelming users.

• Ruggedization in Harsh Conditions — Ensuring sensors remain fully operational under extreme environmental stress: dust, moisture, shock, and temperature swings.

• Disconnected Operations — Maintaining reliable performance without constant connectivity, and ensuring autonomous signal detection under comms-denied conditions.

• Software Integration — Seamlessly integrating sensor outputs with existing battle management systems, SIGINT toolchains, and distributed Command and control (C2) platforms.

Bottom Line:

EW operations have traditionally relied on heavy, centralized systems that were too slow, too brittle, and too reactive to keep pace with evolving threats. Distributed Spectrum is betting that small, smart, and scalable networks—not bigger antennas—will define the next era of electromagnetic warfare.

If their mesh-enabled sensors prove themselves across Indo-Pacific deployments and integrate cleanly into existing C2 and SIGINT frameworks, they could fundamentally reshape how U.S. forces detect, target, and survive in contested environments.

But no single company will solve the DoD’s spectrum challenges alone.
New entrants like Distributed Spectrum must become part of a broader, layered solution—one that turns the kill chain into a kill web, much like China already has.

Because the next fight won’t be won by building the perfect sensor.

It’ll be won by seeing the threat first—and moving faster than it can adapt.

Further Reading

• Breaking Ground Podcast

• The Invisible Battlefield by Colin Hively

• The Primacy of Passive Air Defense

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Defense Tech Signals is your strategic radar for the modern defense industrial base. We track and analyze software-first defense companies that are measurably accelerating military capability development.

1  The views expressed in this newsletter are my own and do not represent the views of the U.S. Navy, Department of Defense, or any government agency. Mention of companies, technologies, or products is not an endorsement or recommendation. The content is for informational purposes only and should not be considered investment advice.

2  These insights are based on data organized on Pryzm, a defense market intelligence platform and CRM.

3  All references to Chinese capabilities are based exclusively on open-source data from publicly available government reports, think tank analyses, and defense media. While capabilities are often understated rather than overstated in public discourse, this article does not draw on any classified information—regardless of any prior or current access we may or may not have.