Case studies

As weather events intensify, this phase of ground operations plays an increasingly strategic role in maintaining on-time departures and overall airport efficiency. With operations servicing multiple airports and over 60,000 aircraft each year, Aeromag must deliver safe, reliable, and consistent deicing services while operating in highly variable environments. Even small inefficiencies can quickly scale, impacting airlines, airports, and passengers alike.

Deicing operations are inherently complex and highly time-sensitive. Technicians continuously reconcile aircraft positioning with deicing truck assignment, glycol blend and volume adjustments based on weather conditions and aircraft models, while respecting workforce constraints such as truck availability, shift planning and mandatory breaks. During severe winter weather, when demand peaks, these decisions can quickly become a bottleneck impacting airport flow, aircraft-on-ground time, and departure times.

Despite having a centralized operations tool, deicing technicians made all logistic decisions manually, relying heavily on experience and intuition in high-pressure situations. Aeromag needed a way to transform its operational data into real-time, optimized guidance to ensure aircraft deicing remained safe, efficient, and consistently executed at scale.

Vooban developed two complementary AI models to optimize Aeromag’s deicing operations. The first is a predictive model that determines the optimal glycol mix for each aircraft based on aircraft type and weather conditions, standardizing usage while reducing waste and maintaining safety standards. The second model focuses on optimizing the scheduling and sequencing of deicing activities by accounting for operational constraints such as truck availability, workforce planning, and aircraft flow.

Both models are integrated into the next generation of Aeromag’s operations platform, GestOp AI. The platform replaces manual decision-making with AI-driven recommendations, simplifies workflows through a decision-support module, and centralizes operational data into a single system. This enables ground teams to act quickly and consistently, improving efficiency and scalability across Aeromag’s airport operations.

The deployment of GestOp AI is already delivering tangible results in real-world operations. In just under three months, Aeromag achieved an average one-minute reduction per deicing operation at the Vancouver and Edmonton airports compared to the previous season. At this scale, even modest time savings translate into meaningful impact, generating more than $250,000 in operational savings for airlines at these two airports alone at the start of the season.

As the platform scales across Aeromag’s network, the impact becomes even more significant. GestOp AI enables time savings of one to four minutes per aircraft. Based on approximately 65,000 aircraft serviced annually, this represents close to 130,000 minutes of optimized aircraft-on-ground time each year. With each minute of aircraft standby estimated to cost airlines around $100 USD, GestOp AI is expected to generate more than $1.2 million in annual savings for Aeromag’s airline partners.

Beyond financial performance, GestOp AI strengthens Aeromag’s operational reliability and sustainability objectives. Reduced ground delays help eliminate bottlenecks during severe weather, improve airport flow, and lower greenhouse gas emissions by minimizing aircraft idle time. By embedding AI directly into daily operations, Aeromag continues its legacy of innovation in deicing technologies while positioning itself as a trusted partner that delivers measurable ROI, operational safety, and environmental impact.

With GestOp AI, Aeromag demonstrates that innovation, efficiency, and sustainability can coexist on the tarmac.