Ozni AI builds AI-native defense systems that combine tactical sensors, multi-INT fusion, and RF exploitation for contested environments. Their attritable hardware runs edge-intelligence architectures with on-board inference across EO/IR, RF, and acoustic streams, delivering real-time situational awareness directly to warfighters. The company also develops machine learning pipelines and advanced signal processing research for defense applications.
Funding
Funding not disclosed
Founders
Product
Problem
Modern warfighters operate in denied and contested environments where traditional sensor systems struggle with data latency, detectability, and integration across multiple intelligence sources. Fragmented sensor feeds and delayed processing limit real-time situational awareness, reducing the speed and accuracy of tactical decision-making in high-stakes operations.
Solution
Ozni AI designs and builds AI-native defense systems that integrate tactical sensors, software, and research into unified intelligence platforms. Their attritable hardware runs purpose-built compute architectures that execute machine learning inference directly on sensor platforms, fusing EO/IR, RF, and acoustic data streams into actionable awareness in real time. Distributed mesh architectures maintain connectivity across contested terrain, while onboard signature management techniques minimize detectability and extend operational endurance. The company's software pipelines span model training to deployed inference at scale, ensuring defense-grade reliability in field conditions.
Target Audience
Primary customers are United States defense agencies and military branches, including DoD program offices and warfighter units requiring tactical sensing, RF exploitation, and multi-INT fusion capabilities for contested environments.
Features
- Edge-intelligence compute architectures enabling multi-modal fusion across EO/IR, RF, and acoustic data streams directly on sensor platforms
- Resilient distributed mesh networks with hardened, SWaP-optimized platforms for sustained operations in denied environments
- Onboard signature management (SIGMAN) techniques that continuously monitor the sensor's environment to reduce detectability and maximize intelligence gain
- Attritable, AI-accelerated tactical sensor hardware designed for contested operational settings
- Production-grade machine learning pipelines covering model training through deployed inference for DoD applications
- Advanced research in signal processing, multi-sensor fusion, and AI systems specific to defense use cases