Airline software provider Accelya has launched an AI-powered real-time order intelligence capability, giving carriers a single, connected view of live order data.
Its FLX ONE Vision software helps commercial, operations, and customer teams see what’s selling, what’s changing, and where issues may emerge.
Accelya says its real-time visibility allows airlines to respond “faster and with greater confidence, turning hours-old reporting into live, actionable insights that protects revenue and service quality”.
Powered by Accelya’s FLX AIViator AI platform, it understands purchasing patterns in real time enabling airlines to see what customers choose to inform pricing or bundle adjustments while interest is high.
It protects performance and service quality to give operations teams real-time insight into changes so they can act early and prevent avoidable disruptions.
And it replaces delayed reports and data stored in separate systems with one shared, live view across teams.
Accelya chief executive Sam Gilliland said: “Airlines are awash with data, but what they need is fast, usable insight. Too often, teams are working from yesterday’s reports to make today’s decisions.
“Real-time visibility changes that completely – it gives people the clarity to act quickly, serve customers better, and avoid unnecessary disruption.”
Accelya launched its modular, cloud-native FLX ONE platform at IATA WPS in 2024 to help airlines modernise their offers and orders at their own pace.
The firm says FLX ONE Vision extends that by showing how live order data can improve decision-making across retail and servicing without major system change.
Accelya says many airlines still face hurdles such as fragmented data, slow reporting cycles, and ‘organisational hesitation’ to change, which FLX ONE Vision was designed to help combat.
The solution, which will be featured at IATA’s WPS and WFS in Istanbul, is currently in beta mode, with some airlines piloting the capability already using live order visibility to uncover operational issues and commercial opportunities.
Early use cases include detecting erroneous fares that would otherwise take days to investigate, identifying premium bookings not tied to loyalty accounts, and monitoring service activities such as waitlists or special requests.
