The solution applies advanced machine learning (neural networks) to help airlines predict demand across their network more accurately than traditional linear regression models.
It allows airlines to personalise ancillary pricing and steer inventory automatically by analysing complete network data and detecting non-linear patterns such as holidays, competitor pricing moves and unexpected demand shifts.
Key benefits include:

• substantially more accurate demand forecasts (reducing manual steering activities by up to -80%), and

• revenue uplift (e.g., direct EBIT gains of +3%)
  It’s cloud-native, scalable to large data volumes, integrates with existing IT setups, and is designed with user-centric workflows so revenue management teams can adopt it with minimal friction.