A major regional flag carrier competes in a fast-moving market where fares shift by the hour and travellers expect offers tailored to them. Its revenue management still ran on legacy infrastructure built around static, rule-based fare buckets. To recover lost yield and price dynamically across fares and ancillaries, the airline partnered with AIQU to build an AI-driven pricing and offer management system that reads the market in real time and personalises every offer.
A major regional flag carrier was running revenue management on legacy infrastructure built around static, rule-based fare buckets. In a volatile post-pandemic market, with competitors cutting prices fast and fuel costs swinging, that approach left money on the table. The airline lost yield and could not price ancillaries dynamically for its highest-value travellers.
Key challenges included:
AIQU implemented an AI-driven dynamic pricing and modern offer management system. The engineering team built deep learning models, including Long Short-Term Memory (LSTM) networks, to read years of booking curves, live competitor fares, and real-time search data. The system gave the carrier the ability to:
The new pricing engine delivered measurable commercial gains.
Autonomous predictive maintenance for one of the region’s largest Tier-1 mobile network operators.