EdgeRunner AI and the U.S. Army's Artificial Intelligence Integration Center have developed EdgeRunner-Camo, a large language model designed specifically for Army use. The open-weight model is fine-tuned on Army-specific data and runs locally in air-gapped environments without requiring cloud-based systems. The model was developed using Impact Level 5 training environments for handling Controlled Unclassified Information. It reduces error rates by up to 37% on six new Army-specific benchmarks created during the partnership. EdgeRunner-Camo will be deployed into EdgeRunner AI's platform and other systems accessible to national security partners. The collaboration aims to provide warfighters with AI capabilities that can operate in denied, disrupted, intermittent, and limited connectivity environments whilst maintaining data security and eliminating third-party API costs.

AI in Military and Defense Market: Army deploys EdgeRunner-Camo LLM. Published: August 18, 2026 EdgeRunner AI and U.S. Army launch army-specific LLM for tactical edge operations. PITTSBURGH, Pennsylvania, United States - August 18, 2026 - EdgeRunner AI, a developer of on-device artificial intelligence platforms for military applications, and AI2C - the U.S. Army's Artificial Intelligence Integration Center - jointly announced the launch of EdgeRunner-Camo, a new open-weight Large Language Model (LLM) purpose-built for Army operations. The development marks a significant milestone in the broader AI in Military and Defense Market, as defense agencies accelerate the transition of AI capabilities from centralized cloud environments to mission-critical, air-gapped tactical edge deployments. EdgeRunner-Camo was fine-tuned on Army-specific data - including datasets from AI2C's existing CamoGPT system - and is engineered to operate locally in Denied, Disrupted, Intermittent, and Limited (DDIL) environments without reliance on third-party cloud-hosted proprietary models. The model was developed through EdgeRunner AI's proprietary pipeline utilizing Impact Level 5 (IL5) training environments when handling Controlled Unclassified Information (CUI) data. According to EdgeRunner AI, the model reduces error rates by up to 37% across six new Army-specific benchmarks created as part of the collaboration. AI2C, headquartered at Carnegie Mellon University in Pittsburgh, Pennsylvania, develops and integrates AI capabilities Army-wide to enhance lethality, achieve operational overmatch, and empower soldiers and units in future conflicts. According to Next Move Strategy Consulting (NMSC), the global AI in Military and Defense Market is expected to reach USD 10.26 billion by the end of 2026. The market is further projected to expand to USD 29.39 billion by 2035, growing at a CAGR of 12.4% from 2026 to 2035, driven by accelerating demand for autonomous systems, edge AI deployments, and mission-critical intelligence platforms across land, air, naval, and cyber domains. Key highlights: * EdgeRunner-Camo is an open-weight LLM fine-tuned on Army-specific data, including AI2C's CamoGPT datasets, and designed for local deployment in air-gapped, DDIL environments without dependence on third-party cloud infrastructure. * The model reduces error rates by up to 37% on six new Army-specific benchmarks, with detailed results and methodology published jointly by EdgeRunner AI and AI2C. * The model was developed using Impact Level 5 (IL5) training environments for handling Controlled Unclassified Information (CUI), ensuring compliance with stringent national security data standards. * The collaboration establishes an ongoing framework between EdgeRunner AI and AI2C to develop best-in-class, mission-specific LLMs deployable across the EdgeRunner AI platform and other national security partner systems. Analyst insight: According to analysts at Next Move Strategy Consulting, the EdgeRunner-Camo launch exemplifies a structural shift in defense AI procurement - from experimental, cloud-dependent deployments toward sovereign, on-device AI systems that can operate in contested and communications-denied environments. NMSC analysts note that the convergence of open-weight model architectures with military-grade data security frameworks - such as IL5-compliant training pipelines - is emerging as a key differentiator in defense AI procurement, as armed forces prioritize data sovereignty, operational resilience, and reduced dependence on commercial cloud infrastructure. This development is consistent with the broader market trend toward edge AI and secure deployment models, which NMSC identifies as a primary growth driver for the AI in Military and Defense Market through 2035. Industry outlook: The launch of EdgeRunner-Camo reflects the U.S. Army's accelerating commitment to embedding AI directly into tactical operations, reducing latency, and eliminating reliance on vulnerable centralized networks. As defense agencies worldwide intensify investment in mission-specific AI models, edge computing infrastructure, and secure data architectures, the competitive landscape is expected to evolve rapidly - with AI-native firms such as EdgeRunner AI increasingly challenging established defense primes in software-defined capability domains. The ongoing collaboration between EdgeRunner AI and AI2C is anticipated to yield additional Army-specific LLM iterations, further advancing the integration of generative AI into command, intelligence, and operational workflows. The global AI in Military and Defense Market is positioned for sustained expansion through 2035, underpinned by multi-domain operational demands, rising defense budgets, and the institutionalization of AI-first force transformation strategies across NATO and allied nations. Prepared By: Sanyukta Deb Sanyukta Deb is a senior content writer and content analyst with expertise in content strategy, audience engagement, and research-driven storytelling. With a strong leadership approach and strategic mindset, she drives content initiatives that strengthen brand communication and audience connection. She combines creativity with analytical insight to develop impactful, value-led content while mentoring collaborative efforts across teams to ensure consistent, meaningful engagement and long-term brand growth across digital platforms. About the reviewer. Debashree Dey is a senior content writer and communications specialist known for crafting audience-focused narratives and insight-driven content strategies. As a published manuscript author, she combines creative storytelling with strategic thinking to strengthen brand messaging, enhance visibility, and drive meaningful audience engagement across digital platforms. With a collaborative leadership approach, she contributes to high-impact communication initiatives that ensure consistency, clarity, and long-term brand value. Outside of work, she finds inspiration in creative projects, design exploration, and storytelling-driven ideas. Share with peers. Its clients. HIVE signs $350M GPU deal, fueling edge AI market growth. OpenSesame expands AI safety training with OSHA partnership. Enterprise AI Market: HIVE BUZZ HPC $350M Deal.

EdgeRunner AI has received Impact Level 6 Authority to Operate accreditation from the US Navy, validating its on-device platform for sensitive military operations. The EdgeRunner OS has also been listed in the Department of the Navy Application and Database Management System, the authoritative registry for approved IT systems. The accreditation enables Navy programmes to integrate SECRET-level data with EdgeRunner's military-specific platform, bringing AI capabilities to disconnected maritime operations. The system runs large language models locally, eliminating connectivity requirements and token limitations. EdgeRunner AI, founded less than two years ago, provides AI solutions for Denied, Disrupted, Intermittent and Limited environments. The company delivers real-time intelligence to tactical operations using LLMs, autonomous agents and computer vision systems.