FlyScout provides autonomous drones and robotic platforms for high‑resolution AI‑driven inspections of industrial assets. The system captures multispectral imagery, runs edge computer‑vision to detect defects in real time, and streams data to a cloud analytics platform that delivers inspection reports, dashboards, and predictive maintenance alerts via web portal or API, reducing inspection time, safety risk, and operational cost for energy, utility, telecom, and infrastructure operators.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial assets such as wind turbines, solar arrays, utility grids, telecom towers, oil & gas facilities, and maritime infrastructure require frequent visual and sensor‑based inspections. Traditional manual inspections are labor‑intensive, expose personnel to hazardous environments, and generate costly downtime due to equipment shutdowns.
Solution
FlyScout delivers autonomous drone and robotic platforms that conduct high‑resolution, AI‑driven inspections without human presence on site. Each platform combines GPS‑precise autonomous flight, obstacle‑avoidance Lidar, and multi‑spectral cameras to capture detailed imagery and sensor data. On‑board edge computing runs computer‑vision models that detect corrosion, blade defects, panel hot‑spots, and structural anomalies in real time. The raw data are streamed to a secure cloud pipeline where advanced analytics generate actionable inspection reports, trend dashboards, and predictive maintenance alerts. Clients can access these insights through a web portal or integrate them via RESTful APIs into existing asset‑management systems. The solution reduces inspection cycles, minimizes safety risks, and lowers overall operational expenditures while maintaining regulatory compliance.
Target Audience
Primary customers are asset‑intensive enterprises in energy (wind, solar, oil & gas), utilities, telecommunications, maritime logistics, and large‑scale infrastructure operators that manage extensive field assets.
Features
- Autonomous navigation stack with GPS/RTK positioning and Lidar‑based obstacle avoidance for safe operation in confined industrial sites
- High‑resolution RGB, thermal, and multispectral imaging payloads delivering sub‑centimeter detail for defect detection
- Edge AI inference engine that runs convolutional neural networks on‑board to flag anomalies during flight, reducing bandwidth usage
- Cloud‑hosted analytics platform that aggregates inspection data, applies deep‑learning models, and produces KPI dashboards and predictive maintenance forecasts
- Open API (REST/GraphQL) and FHIR‑compatible data export for seamless integration with CMMS, ERP, and SCADA systems
- Modular robotic arm attachments for close‑up inspections of hard‑to‑reach components such as turbine blade roots or valve assemblies
- 24/7 autonomous surveillance mode with geofencing and real‑time alerting for security and perimeter monitoring
- End‑to‑end encryption, role‑based access control, and compliance with ISO 27001 and IEC 62443 standards for data security