This is not a market research report. We're a small team building a specific product in a specific part of this market, and we see what we see from that vantage point. What follows is our attempt to honestly characterize the landscape as we understand it — which programs are creating demand, where the commercial product gap sits, and how we think about our position within it. Open-source estimates suggest the addressable market for underground threat detection is meaningful in dollar terms. We won't quote a specific figure because the ones in circulation vary by an order of magnitude depending on what is counted as "subterranean sensing."
Government Programs That Have Shaped Demand
DARPA SIGMA+
DARPA's SIGMA+ program, which extended the original SIGMA radiological detection network, is the most visible public investment in distributed sensor networks for threat detection. SIGMA+ expanded the sensing modalities beyond radiological to include chemical, biological, and explosive precursor detection across wide-area urban networks. The architectural precedent it established — networked autonomous sensor nodes operating persistently without centralized collection infrastructure — is directly relevant to subterranean threat detection, even though the environments are different.
The SIGMA+ work demonstrated at the program level that the defense acquisition community is willing to purchase distributed autonomous sensor systems. It also demonstrated the integration and logistics challenges that accompany wide-area sensor network deployment. Underground applications inherit those integration challenges plus additional constraints from the propagation physics of the underground environment. The program's influence on how we think about network architecture is real, even though SIGMA+ itself does not address underground threats.
Army AMSAA and Underground Threat Work
The Army's Aberdeen Test Center and AMSAA (now referred to under the Army Evaluation Center umbrella for test and evaluation work) have conducted various underground threat detection studies that appear in the public domain through Congressional Research Service reports and RAND analyses. The consistent finding from that work is that persistent, low-signature autonomous sensor coverage is the operationally preferred approach over periodic survey-based detection. Fixed large-format systems (ground-penetrating radar arrays on vehicles, airborne synthetic aperture radar) are operationally disruptive and can't provide the persistent coverage that autonomous node networks offer.
The Army's tunnel threat work since the Gaza and Iraq/Afghanistan campaigns has also driven development requirements toward systems that can operate in contested and denied access environments without requiring frequent human maintenance access to sensor nodes. That requirement — extended autonomous operation without service access — directly shaped the battery life, IP rating, and sealed enclosure specifications we discussed in the field notes piece earlier this year.
Israeli Tunnel Detection Programs
The Israeli defense establishment has the most operationally mature tunnel detection capability in the world, developed under operational pressure at the Gaza boundary and refined over more than a decade of deployments. The broad outlines of their approach are discussed in publicly available Israeli Defense Ministry and IDF press materials: seismic array infrastructure combined with above-ground GPR survey and human intelligence. The specific technical details of their seismic system remain classified or unpublished.
We don't make claims about the specific performance of the Israeli systems or the details of their architecture beyond what appears in open literature. What we can say is that the operational validation of seismic-based tunnel detection at scale, demonstrated over multiple years of active operations, provides the clearest real-world proof point that this approach works when properly implemented. The gaps that remain — false positive management at scale, rapid deployment to new threat sectors, autonomous response capability — are the areas where commercial development is needed and where the Israeli military approach, built for a specific fixed geography, has limitations.
The US-Mexico Border Detection Gap
The US-Mexico border represents one of the most documented subterranean threat environments outside a declared conflict zone. CBP and DEA have documented dozens of cross-border narco tunnels over the past two decades, ranging from rudimentary hand-dug passages to elaborately reinforced corridors with rail systems, ventilation, and electrical infrastructure. Open-source estimates from CBP press releases suggest discovery of one to three major tunnels per year in the San Diego and El Paso sectors alone, which likely represents a fraction of active tunnels rather than the total.
The detection infrastructure on the US side is sparse. Periodic GPR survey runs and sensor probe placements at known tunnel entry points address known threat locations. Persistent monitoring of new terrain — the majority of the border — relies primarily on surface-level detection (cameras, ground sensors, seismic surface arrays) that have poor detection probability for well-constructed tunnels below 6–8 meter depth. The gap is specifically in below-depth, wide-area, persistent monitoring.
The operational requirement for border tunnel detection differs from military tunnel scenarios in one important way: extended time-to-discovery is acceptable if discovery is eventually certain. Narco tunnels are capital-intensive to construct; discovery after 18 months is costly to the operator even if not immediately. Military tunnel threats require faster response because the tactical use window is short. This difference in acceptable detection latency affects the precision-recall tradeoff and the alert response protocol design. Border applications can tolerate higher confidence thresholds and longer dwell-time filters; military applications require faster response at some cost to false positive rate.
Where Commercial Products Stand
The commercial product landscape for underground threat detection is sparse. The companies with the most deployable technology are either large defense contractors building fixed GPR infrastructure (vehicle-mounted, expensive, not persistent) or geophysical surveying companies whose equipment is designed for mineral exploration rather than persistent security monitoring. The autonomous node network architecture — small, self-powered, mesh-networked, designed for persistent unattended deployment in a threat environment — does not have a mature commercial product in it.
Several academic spinouts and small defense tech companies have demonstrated prototypes of this general class, but commercial production and procurement-ready capability is limited. The gap between "demonstrated in controlled conditions" and "deployable at scale under operational constraints" remains wide in this category. The companies that have gotten closest are typically backed by SBIR/STTR funding chains and have not yet completed the transition from development to production. We include ourselves in that characterization.
The integration challenge is also significant. Defense customers don't want a seismic sensor array that requires custom integration into their command and control infrastructure. They want a system with defined data interfaces, defined alert protocols, and a support organization capable of maintaining it over a multi-year contract period. Small companies building novel hardware have to demonstrate not just that the hardware works but that the surrounding services and support organization exist. That's a legitimate procurement concern, and it is one of the barriers separating the current landscape of prototype-class products from fielded capability.
Where Tarysar Fits: Small Autonomous Nodes vs. Large Fixed Installations
Our product positioning is specifically in the autonomous node network architecture — not the large GPR vehicle systems or fixed seismic infrastructure, but the disaggregated, rapidly deployable, self-powered mesh that can be established in hours by a small team. The tradeoff we accept is that individual nodes have lower detection sensitivity than large fixed arrays. The tradeoff we gain is deployment flexibility, reduced logistics footprint, and the ability to establish coverage in environments where fixed infrastructure is not feasible — because the access to install it doesn't exist, because the threat environment makes maintenance impractical, or because the terrain changes faster than fixed infrastructure can be relocated.
We're not claiming this is the only valid architecture or that it's better than fixed arrays for all use cases. Fixed seismic infrastructure with large-format geophones and hardwired power has real performance advantages in stable, accessible environments where long-term installation is feasible. Our architecture is optimized for the cases where that's not the operating condition — which, based on our conversations with the procurement community, is a significant fraction of the actual requirements.
Market size estimates vary widely — open-source estimates suggest the addressable US government market for underground threat detection systems is in the range of several hundred million dollars over a five-year horizon, based on Congressional appropriations data and publicly announced program budgets. We don't have the independent analysis to validate that figure. What we believe on the basis of program activity, documented threat frequency, and the procurement conversations we've had is that there is genuine unmet demand that exceeds current commercial supply — and that the small autonomous node architecture addresses a specific gap that neither the legacy fixed-infrastructure vendors nor the emerging drone-survey approach fills. How large that gap translates to in procurement dollars remains to be demonstrated rather than asserted.