We bring together multi-modal data to identify flaws and maintenance needs on a near real-time basis.
We use multi-sensor data fusion and neural networks to identify features of interest such as power lines and roof damage, and monitor critical infrastructure through automatic change detection algorithms.
We utilize deep layering and neural networks to detect flaws in NDI images of additively manufactured and other mission-critical hardware.
We merge computer vision with low SWaP processors to provide real-time capabilities for dimensional and other types of "as-built" inspections.
Our highly-integrated, semi-custom spacecraft architecture enables high payload volumes and responsive flexibility for a wide range of sensors.
Our neural net algorithms provide edge intelligence in aerial and space-borne platforms using low-SWaP processors optimized for on-board applications.