NEURON: Mesh Network for Tactical Edge Embodied AI

NEURON: Mesh Network for Tactical Edge Embodied AI is sponsored by Department of Defense (DOD), USAF. Phase I SBIR award to develop a mesh network system combining AI and machine learning for tactical edge operations.

4817 RADFORD AVE PMB 98160 VALLEY VILLAGE, CA, 91607-3720 Socially and Economically Disadvantaged: No Year of first award: 2025 Up to 10 of the most recent awards are being displayed. To view all of this company's awards, visit the Award Data search page.

CORTEX: AI/ML for Tactical Edge Embodied AI China’s drone army is amassing at an astronomical rate, developing many capabilities and is “10 times larger than Taiwan and the U.S. combined. ”China threatens to overrun the warfighter and its allies with superior drone numbers by producing them at rates which the United States may never match.

U.S. UAS systems are inefficient, unreliable, and require a high operator cognitive load, all while putting too many operators in danger. Unless another solution is adopted, the U.S. will be overrun by the enemy’s UAS invasion.

Combining Artificial Intelligence and Machine Learning with an advanced mesh network system, Gambit can give the USAF a solution that drastically reduces an operator’s cognitive load, lets a single user operate 50+ systems, and allows systems to learn from their environment to accomplish tasks on their own while astronomically outperforming human decision-making.

Gambit’s solution will allow the USAF to combat a numerically superior Chinese drone force with more efficient decision-making while reducing the number of operators put in harm’s way. We will execute a 3-month systematic and intensive feasibility study of Gambit’s CORTEX AI/ML solution to establish the scope of modifications needed for the Phase II to adapt the core technology to fit the End-User's mission.

NEURON: Mesh Network for Tactical Edge Embodied AI Russian Electronic Weapons (EW) are wreaking havoc across Eastern Europe, disrupting GPS systems and leaving high-tech U.S. weapons ineffective.

Current USAF UAS capabilities operate in an archaic and inefficient manner, requiring a high cognitive load from operators to work only a few systems, meaning more operators putting their lives in danger working archaic UAS systems that will be rendered inert by Russian EWs. Unless a new solution is put into place, Russian EW and Chinese drone capabilities will outpace the United States.

Combining Artificial Intelligence and Machine Learning with an advanced mesh network system, Gambit can give the USAF a solution that reduces an operator’s cognitive load, let’s a single user operate 10+ systems, and allows systems to learn from their environment to accomplish tasks on their own while remaining resilient to jamming and EWs.

Gambit’s solution will allow the USAF to combat EW and drone threats on a massive scale, leading to fewer operators risking their lives operating inefficient UAS systems in dangerous forward-deployed locations.

We will execute a 3-month systematic and intensive feasibility study of Gambit’s NEURON mesh network solution to establish the scope of modifications needed for the Phase II to adapt the core technology to fit the End-User's mission.? Spectrum Supremacy Utilizing a Mesh Network: NEURON The Big Picture: In January 2024, US air defenses failed to shoot down a hostile drone at Tower 22, a military outpost in Jordan.

The drone struck a housing unit, exploding on impact. 3 US soldiers were killed and at least 40 others were injured. Adversarial comms-reliant technology is advancing rapidly, and in many cases is outpacing U.S. capabilities, highlighting horrific gaps in national security that the United States faces today.

If the DoD does not adopt new methods of defending against these comms-reliant technologies, many US soldiers will die unnecessary deaths in the impending three-front war. Technical Problem: The United States military's safety and effectiveness is threatened by adversarial comms-reliant technology. Drones, for example, are often fast, cheap, and efficient while defense solutions are slow, expensive, and inefficient.

All adversarial military capabilities in some form rely on comms, which allow adversaries to compete with the United States on equal footing. The warfighter needs a solution that denies adversarial comms, allowing the warfighter the substantial upper hand in conflict. Solution: An autonomous, comms-jamming drone swarm.

Our solution is a mesh network technology for UAS systems that, when paired with our enabling AI/ML technology, allows UAS systems, such as drones, to operate intelligently and independently, providing the USAF with an autonomous mobile EW capability. This architecture allows far more systems to be piloted by far fewer operators, increasing operator efficiency by 6000% and reducing operator training time by 93%.

Our solution enables UAS systems to form jam-resistant mesh networks that allows units within the network to communicate reliably even within contested environments. In essence, it will use an autonomous drone swarm to ensure friendly comms while denying enemy comms. By adopting our solution, the warfighter can undercut adversarial technology and always have the upper hand in conflict.

Dedicated Counter UAS Opposing Forces Utilizing AI/ML: CORTEX Big Picture: In December 2023, dozens of unidentified drones entered Langley Air Force Base airspace, uncontested, for more than two weeks. None were shot down, and the identity of the operators remains unknown.

The United States' counter-UAS (c-UAS) capabilities have failed to prevent hundreds of drone incursions at military installations such as Langley, Hill, and Wright-Patterson AF Bases over the past few years, according to NORTHCOM. Alarmingly, these reported incidents are just the tip of the iceberg; General Gregory Guillot warns that "there's significantly more incursions that we don't see."

The United States stands on the brink of a disastrous three-front war that will be dominated by drone warfare, leaving US national security alarmingly vulnerable due to the inadequacy of counter-UAS capabilities. If c-UAS systems are not rapidly trained and developed to meet this threat, the warfighter will be overrun by hordes of adversarial drone swarms.

Technical Problem: US counter-UAS systems are falling behind the rapid advancements in UAS technology. Training programs are outdated and fail to simulate the intelligent and quick systems encountered in the field. This results in c-UAS capabilities lagging, creating security gaps and unvalidated defenses.

Without effective training and evaluation methods, national security is at significant risk. An advanced training solution is crucial to develop robust c-UAS systems. Solution: Our solution is an AI/ML solution that enables coordinated autonomous swarms of heterogeneous UAS platforms through advanced reinforcement learning and multi-agent coordination.

It enables a single operator to control 10 or more diverse UAS platforms simultaneously, executing sophisticated tactics, techniques, and procedures based on documented adversary behaviors.

By deploying our solution as a Red Team Opposition Force, the system provides standardized, repeatable c-UAS testing capabilities across DoD installations, enabling comprehensive evaluation of defensive systems against realistic coordinated drone attacks representing EW, EMP, ballistic, and cyber vulnerability profiles.

The AI/ML foundation ensures continuous adaptation and learning from each engagement, allowing our solution to evolve with emerging threats while simultaneously training both c-UAS systems and operators through authentic adversarial scenarios.

This dual-use capability helps the USAF develop more effective c-UAS technologies by providing validated performance metrics and identifying defensive gaps that traditional testing methods cannot reveal, ultimately enhancing force protection and defending US personnel and assets against increasingly sophisticated UAS threats.