Thomas Kim

Nearthlab develops AI-powered drone inspection software for wind turbines and critical infrastructure, using computer vision models to automatically detect and classify structural defects from aerial images captured by inspection drones, replacing manual rope access inspection with automated drone-and-AI workflows that are safer, faster, and more consistent. The Seoul company platform processes blade inspection imagery to identify cracks, erosion, and lightning strike damage across the turbine blade surface.\n\nThe company raised approximately $15 million in venture funding and has deployed its inspection platform across wind farms in South Korea, Europe, and North America. Nearthlab has built partnerships with drone hardware manufacturers and wind energy operators, positioning the platform within existing operational maintenance workflows. The company reports that its AI defect detection achieves accuracy comparable to expert human inspectors on standardised blade damage classification tasks.\n\nNearthlab competes in the AI infrastructure inspection market against Cyberhawk, Apellix, and DroneBase, as well as in-house drone inspection programs at major wind turbine manufacturers including Vestas and Siemens Gamesa. The wind energy sector represents a growing market for automated inspection as global installed wind capacity expands and blade maintenance costs become a significant component of wind farm operating expenditure. AI-powered defect detection that can prioritise maintenance work orders based on damage severity provides direct cost reduction for wind farm operators managing large fleets of turbines across geographically distributed sites.