Resilient AI for Contested Environments

Hardened models with certified defenses against data poisoning, evasion attacks, and prompt injection, validated using the MITRE ATLAS framework. Ensures AI decision-making remains reliable under active manipulation.

AI systems engineered to maintain core functionality in Disconnected, Intermittent, and Low-bandwidth (DIL) environments and under active communication jamming, using adaptive edge inference and local model fallbacks.

Privacy-preserving collaborative training across distributed units or allied forces without centralizing sensitive operational data. Ensures model improvement while maintaining strict data sovereignty. Learn more about our Federated Learning Systems Engineering.

Optimized Small Language Models (SLMs) and computer vision models deployed on ruggedized, low-SWaP hardware for real-time intelligence processing and decision support at the tactical edge. Explore our SLM Edge Deployment capabilities.

Proactive, ongoing adversarial testing of your operational AI systems to identify and remediate novel vulnerabilities before they can be exploited, ensuring continuous hardening of mission-critical models.

End-to-end secure model development, deployment, and monitoring pipelines within air-gapped or accredited cloud environments. Full model lineage, version control, and drift detection for auditability. Integral to our Confidential Computing for AI Workloads approach.

Hardened systems that fuse and analyze classified intelligence from text, imagery, audio, video, and sensor feeds within air-gapped or secure enclave environments. Enables unified battlefield analysis without data exfiltration risk.

Development and adversarial testing of AI for autonomous air, ground, and maritime systems. Includes counter-drone swarms and patrol vehicles with robust fail-safe protocols and resilience against electronic warfare.

Deployment of unsupervised ML and anomaly detection models engineered for air-gapped networks. Identifies novel insider threats and sophisticated malware that evade traditional signature-based tools.

Low-latency, resilient ML for secure, adaptive communications. Includes AI for dynamic spectrum management, LPI waveform optimization, and real-time jamming detection and mitigation in contested EM environments.

Specialized computer vision pipelines for automated analysis of satellite, aerial, and drone imagery at scale. Enables real-time object detection, change detection, and activity monitoring for tactical intelligence.

Deep learning systems for automatic classification, demodulation, and geolocation of complex RF signals in congested spectrums. Transforms raw electromagnetic data into actionable intelligence for electronic warfare.