EI2 is a defense technology company developing proprietary computer vision models and autonomy algorithms for unmanned aircraft. Our modular, cross-platform engines are designed to improve perception accuracy, response speed, and navigation safety on compatible platforms. Integrate the capabilities your mission needs into your existing stack.
Our implemented component architecture separates sensing, perception, mapping, planning, avoidance, safety, and mission functions. Select capabilities independently or together, subject to their input dependencies. Specialized AI models and application-specific evaluation guide development; readiness varies by configuration.
Proprietary computer vision models and algorithms for object detection, classification, multi-object tracking, identification, and visual scene understanding.
Developing custom models using representative training data, held-out accuracy measurement, and edge-inference evaluation. Target tasks include airborne object detection, infrastructure monitoring, and application-specific perception. Model readiness varies by task and conditions.
Supported functionality includes path planning, static-obstacle avoidance, dynamic-object collision avoidance, GPS-denied visual-inertial navigation, 3D environment mapping, trajectory planning and control, and flight-controller integration. Independent safety supervision checks movement requests; recovery behavior is evaluated in defined simulation scenarios.
AI-based perception works alongside conventional robotics algorithms, planning, and control. GPS-denied visual-inertial navigation uses onboard cameras and IMU measurements to estimate motion without satellite positioning. Explore navigation →
These are development and evaluation objectives, not established performance gains. Each pilot defines a baseline, target metrics, operating conditions, and a compatible hardware configuration. We report measured results with their test scope and limitations.
Measure detection precision and recall, false-alarm rates, tracking continuity, and identity switches on representative, held-out data.
Measure end-to-end perception-to-control latency and processing rate on the target onboard hardware.
Evaluate collision and near-miss rates, minimum obstacle clearance, and avoidance success within defined test scenarios.
Compare mission completion rates, route length, flight time, and human interventions under matched conditions.
Profile compute utilization, memory use, and power consumption for each tested model and hardware configuration.
Track integration effort and validated combinations of flight controllers, sensors, compute hardware, and capabilities.
Our primary focus is defense OEMs, systems integrators, and government development programs. Enterprise and local-government applications are additional opportunities. These are opportunities for development and evaluation, not claims of customers, contracts, deployments, or validated production capabilities.
Defense OEMs, systems integrators, and government programs: explore mission-specific technology through scoped development and validation.
Integrate the AI capabilities your platform needs. EI2’s modular architecture is designed to work alongside existing flight controllers, sensors, and mission software—without requiring customers to replace their entire stack. Depth camera, stereo camera, and LiDAR support provide sensing options for compatible platform configurations.
Start with vision alone, static avoidance with its required sensing and map inputs, or a combined autonomy configuration. Selectable components share explicit input and lifecycle requirements. Onboard edge deployment and hardware flexibility remain subject to platform compatibility and qualification.
Flight-controller adapters separate reusable autonomy logic from platform-specific interfaces. PX4 and ROS 2 are our primary integration environment. A limited ArduCopter control adapter is implemented; ArduPilot autonomous navigation and camera avoidance remain unavailable. Additional vendor adapters require development and validation.
CPU-only execution supports ARM and Intel GPU-less boards, with NVIDIA and Qualcomm compute options for supported configurations. Configurable algorithms adapt the pipeline to mission and compute requirements, while independent checks evaluate sensor freshness, stopping distance, trajectory clearance, and control authority. Support and performance are established per tested configuration.
EI2 develops and licenses proprietary AI models and autonomy technology. We work with your engineering team on integration, requirements, and validation. We do not manufacture drones.
Work with us to establish what the system should do, where it struggles, and what it would take to deploy it.
Define the mission, platform, operating envelope, and baseline. Set targets for detection accuracy, response latency, clearance, mission completion, and onboard compute.
Prepare the data, develop the pipeline, and evaluate accuracy, false positives, and latency on held-out footage.
Review the evidence together and scope software integration, validation, and support. EI2 leads integration of its software with your team; partners provide the aircraft and hardware expertise.
Building an unmanned aircraft platform for defense? Scope an evaluation of proprietary vision models and autonomy algorithms against your mission requirements.