FlightLevel Technologies offers Runway Vision, an AI‑driven platform that fuses computer‑vision, LiDAR and radar sensors to track aircraft and ground vehicles on airport surfaces in real time. The solution delivers a cloud‑native dashboard, automated landing‑fee calculation, noise‑impact mapping, predictive collision alerts, and standard APIs for integration with existing airport IT systems.
Funding
Funding not disclosed
Founders
Product
Problem
Airports must continuously monitor aircraft and ground vehicle movements to ensure safety, optimize runway utilization, and accurately bill landing fees, yet legacy systems rely on manual logs and disparate sensors, leading to data gaps, delayed reporting, and increased collision risk.
Solution
FlightLevel Technologies delivers Runway Vision, an AI‑driven airport management platform that fuses computer‑vision algorithms with robotic sensor networks to capture every movement on the airfield in real time. The platform aggregates raw telemetry into a cloud‑native analytics dashboard that supports both live operational views and historical trend analysis. Automated landing‑fee calculation leverages precise aircraft identification to generate billing records without manual entry. Integrated noise‑monitoring modules map acoustic footprints to support regulatory compliance, while predictive anti‑collision analytics issue early alerts to controllers and ground crews. All data streams are secured via end‑to‑end encryption and exposed through standard APIs for seamless integration with existing airport IT stacks.
Target Audience
The primary customers are commercial airport operators, airfield management teams, and ground‑handling service providers that require integrated, data‑driven oversight of runway activity.
Features
- High‑resolution AI vision system combined with LiDAR and radar‑based robotics to track aircraft and ground vehicles with sub‑meter accuracy
- Real‑time event stream processing pipeline that feeds a customizable web dashboard for operational monitoring and post‑flight analytics
- Automated landing‑fee engine that matches transponder IDs to fee schedules and generates invoicing data automatically
- Noise‑impact mapping tool that correlates flight paths with decibel measurements and produces compliance reports
- Predictive anti‑collision module using machine‑learning models to detect trajectory conflicts and issue proactive alerts
- RESTful and GraphQL APIs for integration with ATC systems, ERP, and third‑party analytics platforms
- Cloud‑first architecture with role‑based access control, audit logging, and HIPAA‑grade encryption for data at rest and in transit
- Modular licensing that allows airports to enable or disable specific analytics components per operational need