Aeroport AI delivers AI-driven automation for airline and airport ground‑handling operations, using existing ramp and jet‑bridge cameras to capture real‑time data. Their platform provides delay alerts, timing predictions, and risk notifications to streamline turnaround, reduce costs, and lower emissions, while also offering FOD detection and perimeter monitoring.
Funding
Funding not disclosed
Founders
Product
Problem
Airline and airport ground‑handling operations rely on manual monitoring and fragmented data sources, leading to frequent turnaround delays, higher operational costs, and increased safety risks such as foreign‑object debris (FOD) incidents.
Solution
Aeroport AI uses existing ramp and jet‑bridge cameras to capture real‑time video of apron activities. Deep‑learning computer‑vision models process the footage to generate delay alerts, timing predictions, and risk notifications for ground‑handling tasks. Time‑series analysis forecasts turnaround durations, enabling proactive resource allocation. The platform also detects FOD and monitors perimeter security, helping to prevent accidents and reduce emissions associated with prolonged aircraft ground time. All insights are delivered through a dashboard that integrates with airline and airport operational systems, supporting data‑driven decision making.
Target Audience
Primary customers are airline ground‑handling teams and airport operations managers responsible for apron workflow efficiency and safety.
Features
- Real‑time video ingestion from existing airport cameras without additional hardware
- Deep‑learning computer‑vision algorithms for automated detection of FOD and perimeter breaches
- Predictive analytics that provide delay alerts and turnaround time forecasts
- Risk‑alert engine that flags unsafe ground‑handling conditions and potential injuries
- Emissions‑impact estimation to quantify environmental benefits of reduced ground time
- Integration APIs for seamless connection to airline and airport operational platforms