SBIR

The Small Business Innovation Research Program (SBIR) is a U.S. federal funding mechanism designed to accelerate innovation by enabling small businesses to conduct research and development with strong commercialization potential. Administered across agencies such as Department of Defense, National Science Foundation, and National Institutes of Health, SBIR is structured in three phases: Phase I establishes technical feasibility, Phase II expands development and prototyping, and Phase III focuses on commercialization—often without additional SBIR funds. The program is non-dilutive, meaning companies retain equity while gaining early validation, making it a strategic pathway for startups operating in deep tech, defense, healthcare, and advanced manufacturing.

RailSight XR

Groundbreaker Solutions’ RailSight XR is a self-contained, goggle-based augmented reality system that enables a single maintainer to detect, assess, and repair rail-line damage in real time—even in low-visibility, GPS-denied, or electronically contested environments. By fusing multi-modal sensors—including LiDAR, depth cameras, thermal, hyperspectral imaging, and mmWave radar—with on-device AI, the system generates a live 3D “digital twin” of rail infrastructure, automatically identifying components, classifying gauge, and estimating crater volumes with high precision. This hands-free platform replaces manual inspection methods with actionable AR overlays, reducing repair timelines from hours to minutes while maintaining full edge autonomy and operational security. Designed for both defense and commercial rail applications, RailSight XR represents a step-change in infrastructure resilience and field-ready intelligence.
Under consideration by US Army since June 2025

Archetypes and Analytics: Building AI-Driven Cognitive Warfare Assessment Tools

Groundbreaker Solutions has proposed an advanced cognitive warfare assessment platform that leverages large language models and multimodal analytics to detect, interpret, and influence narrative dynamics across complex information environments. The concept integrates Drama Theory, Jungian archetypes, Hofstede’s cultural dimensions, and appraisal-based emotional modeling to generate “emic” insights—recommendations that reflect how target audiences actually perceive and respond to messaging. By processing text, video, audio, and social data streams in near real time, the system constructs adaptive population models and AI-driven personas capable of identifying key dilemmas, forecasting sentiment shifts, and shaping strategic communication. If pursued, this approach would provide military and civilian operators with a powerful decision-support tool to navigate and influence cognitive domains with greater precision, cultural awareness, and operational effectiveness.
Positive Feedback from USAF but ultimately rejected in March 2025

Cloud-Native Modular Cognitive Warfare Simulation Platform

Groundbreaker Solutions has proposed a cloud-native, modular cognitive warfare simulation platform that delivers immersive, multi-modal training by combining cyber operations with real-time information and influence campaigns. Built on a hybrid simulation engine that integrates agent-based modeling with LLM-driven narrative generation, the system creates dynamic, adaptive scenarios for Red, Blue, and White teams, enabling realistic exercises that reflect modern hybrid threats. A reinforcement learning–based control layer adjusts scenarios in real time, while integrated data pipelines blend live and synthetic inputs to simulate complex environments such as misinformation campaigns, insider threats, and coordinated cyber-attacks. Designed with zero-trust security, scalable microservices architecture, and full auditability, the platform provides a “train as you fight” capability that enhances decision-making, resilience, and operational readiness across defense and commercial sectors.
Positive Feedback from US Navy but ultimately rejected in August 2025

SWARM-IQ: Autonomous Cognitive Mapping Mesh for DDIL Operations

Groundbreaker Solutions has proposed a resilient, AI-enabled platform for detecting, analyzing, and responding to chemical, biological, radiological, and nuclear (CBRN) threats through the fusion of distributed sensor networks and edge intelligence. The concept integrates real-time data ingestion from heterogeneous detectors with advanced analytics, machine learning models, and geospatial processing to identify anomalies, characterize threats, and provide actionable insights to operators in contested or degraded environments. By emphasizing edge autonomy, secure communications, and rapid situational awareness, the system is designed to operate with limited connectivity while maintaining high-confidence detection and decision support. If advanced, this approach would enhance force protection, accelerate response timelines, and improve operational effectiveness across defense, emergency response, and critical infrastructure domains.
Rejected by Defense Threat Reduction Agency September 2025

Model-Agnostic LLM Architecture Powered by Azure Cosmos DB Graph API with a Power BI Front End

Groundbreaker Solutions’ model-agnostic LLM architecture delivers a real-time, decision-support platform that transforms fragmented operational data into context-aware, actionable intelligence for commanders. Built on a globally distributed knowledge graph using Azure Cosmos DB’s Gremlin API, the system ingests structured and unstructured data—from battlefield telemetry to logistics and readiness metrics—and automatically maps relationships, provenance, and classification into a unified data layer. A flexible LLM interface then retrieves relevant context, constructs grounded prompts, and generates concise, bias-mitigated insights, while remaining decoupled from any single AI vendor to ensure long-term adaptability. Integrated with near-real-time analytics via Synapse Link and intuitive Power BI dashboards, the platform reduces cognitive load, accelerates decision cycles, and enables secure, explainable AI-driven operations across tactical and enterprise environments.
Rejected by US Army February 2026

AI-Driven Spectrum Monitoring and Awareness for Tactical Units

Summary | Full Whitepaper

Groundbreaker Solutions has proposed an AI-driven spectrum monitoring and awareness system designed to give dismounted warfighters real-time visibility into the radio frequency (RF) environment directly at the tactical edge. By integrating deep learning–based signal classification, emitter localization, and portable software-defined radios with the Android Tactical Assault Kit (ATAK), the system enables operators to detect, identify, and map signals such as Wi-Fi, LTE, and push-to-talk radios in milliseconds—even in congested or contested environments. The platform emphasizes low size, weight, and power constraints, seamless integration with existing radios, and intuitive user interfaces that minimize cognitive load while providing actionable alerts and pattern-of-life insights. If advanced, this approach would eliminate reliance on rear-echelon analysis, significantly accelerate decision-making, and enhance force protection, while also offering dual-use applications in public safety, telecommunications, and spectrum management.
Rejected by DARPA June 2025
Referenced by Duke Defense Design Studio August 2025

MetaMesh Wardriving SWAT Swarm

Groundbreaker Solutions has proposed the MetaMesh Wardriving SWAT Swarm, an autonomous electromagnetic warfare system that combines micro-drone swarms and deployable “anchor” nodes to detect, classify, geolocate, and disrupt enemy RF emissions in real time within contested and GPS-denied environments. Leveraging onboard AI, software-defined radios, and a resilient UWB mesh network, the system triangulates hostile signals with high precision and integrates directly into ATAK/Blue Force Tracker to provide actionable situational awareness across the force. Once threats are identified, anchor nodes enable targeted jamming and sophisticated deception operations—such as mimicking enemy networks—to disrupt communications and gather intelligence. If advanced, this approach delivers a unified “detect, deceive, disrupt” capability that enhances force protection, accelerates decision-making, and provides a scalable, dual-use platform for defense, law enforcement, and critical infrastructure security.
Rejected by SOCOM December 2025

Deceive, Detect, Disrupt: Autonomous Digital Twin Decoy Networks for Cyber Threat Engagement

Groundbreaker Solutions’ autonomous digital twin decoy network platform delivers a next-generation cyber defense capability that shifts organizations from reactive security to proactive adversary engagement. Built on Azure Digital Twins and deployed via fully automated Infrastructure-as-Code, the system creates a high-fidelity, AI-driven replica of enterprise networks that dynamically mimics real user behavior, traffic patterns, and system activity. Advanced generative models and reinforcement learning continuously adapt the environment in real time, deceiving even sophisticated attackers while capturing detailed threat intelligence on their tactics and tools. By isolating adversaries within a controlled, lifelike sandbox, the platform enables defenders to detect, disrupt, and study attacks without risk to real systems—transforming every intrusion attempt into actionable intelligence and strengthening overall cyber resilience across defense and commercial environments.
Rejected by USAF September 2025

From Slides to Smart Courses: Revolutionizing Training with Azure and Generative AI

Groundbreaker Solutions has proposed GenAI4C, an AI-driven platform that transforms legacy training materials—such as PowerPoint slides and documents—into fully interactive, modern e-learning courses within existing learning management systems like Moodle. Built on a secure, cloud-native Azure architecture with modular microservices, the system combines advanced content parsing, retrieval-augmented generation, and multimedia synthesis to automatically generate lessons, assessments, and immersive training scenarios while maintaining strict human-in-the-loop oversight for quality and compliance. The platform streamlines course creation, enhances learner engagement, and enables rapid, scalable deployment of training content, providing a modernized, efficient approach to military education and workforce development aligned with evolving operational needs.
Rejected by the US Navy November 2025

Project Sentient Nexus: AI-Driven Knowledge Integration for Combat System Interoperability

Groundbreaker Solutions has proposed Project Sentient Nexus, an AI-driven platform that automates the creation and maintenance of a unified data model for naval combat systems, addressing longstanding challenges in interoperability across sensors, weapons, and command-and-control networks. By leveraging machine learning, natural language processing, and semantic reasoning, the system transforms unstructured technical documentation into standardized, machine-readable schemas and dynamic knowledge graphs, enabling real-time data fusion and decision support. Integrating multiple defense and data standards—including NIEM, UCore, DoDAF, RDF/OWL, and STIX—the architecture ensures scalable, secure, and future-proof interoperability across DoD and allied systems. If advanced, this approach would significantly reduce the cost and complexity of system integration while enhancing operational awareness, cybersecurity resilience, and mission effectiveness in complex, multi-domain environments.
Rejected by US Navy April 2025

AirForce EcoIntel: AI-Powered NEPA Advisor

Groundbreaker Solutions has proposed an AI-powered NEPA Assistant that reimagines environmental compliance as a faster, policy-grounded, and fully auditable process. The concept combines retrieval-augmented generation, StratML-informed knowledge graphs, geospatial impact modeling, and cryptographic provenance tracking to produce legally defensible analyses, identify site-specific risks, and streamline public comment review—all within a secure, zero-internet environment. If advanced, this approach would significantly reduce timelines and costs while enabling the Air Force and other agencies to accelerate mission-critical projects without compromising regulatory compliance.
Rejected by USAF November 2025

Revolutionizing Defense Supply Chain Resilience: Implementing Blockchain-Based Smart Contracts for Strategic Risk Management

Groundbreaker Solutions has proposed a blockchain-based smart contract framework to modernize defense supply chain risk management by introducing real-time visibility, automated enforcement, and immutable tracking across procurement, logistics, and sustainment processes. Built on a permissioned blockchain architecture integrated with cloud services, ERP systems, and secure data layers, the approach enables automated contract execution, vendor accountability, and tamper-proof audit trails while maintaining strict compliance with DoD regulations such as ITAR and NISPOM. By leveraging smart contracts to trigger actions like delivery validation, payments, and quality assurance, the system reduces human error, improves efficiency, and strengthens resilience against disruptions and adversarial interference. If advanced, this solution would provide a scalable, secure foundation for defense supply chains while offering significant dual-use potential across industries requiring transparency, compliance, and risk mitigation.
Rejected by US Navy June 2025