Air France-KLM Group will deploy GE Aerospace's Fuel Insight platform across Air France, Hop! and Transavia France under a five-year agreement, extending the fuel analytics solution to the group's entire airline portfolio.

The agreement builds on existing Fuel Insight deployments at KLM, KLM Cityhopper (KLC), Martinair and Transavia Holland. With all Air France-KLM operating certificates using the platform, the airline group expects to improve collaboration and share fuel-efficiency best practices across its operations.

Fuel Insight is designed to help airlines analyze fuel consumption, optimize flight planning and monitor the effectiveness of fuel-saving initiatives. The software integrates with flight planning systems and provides operational analysis tools to identify efficiency opportunities, validate improvements and support sustainability reporting.

"Fuel remains one of the biggest drivers of airline operating costs, and it's also central to sustainability progress," said Andrew Coleman, president and general manager of GE Aerospace Software as a Service. He said the platform helps airlines identify fuel-saving opportunities, measure results and turn successful initiatives into repeatable operational practices.

Christian Gauthier, executive vice president of transformation and sustainable development at Air France, said adopting a common analytics platform across the group's airlines will allow teams to work from the same data, accelerate fuel-saving initiatives and strengthen emissions reporting.

According to GE Aerospace, Fuel Insight has supported an estimated 1.4 million metric tons of carbon dioxide savings across airlines using the platform.

GSW Takeaway: While the announcement centers on airline software, it reflects the growing role of operational data and analytics in improving efficiency across aviation. Better fuel planning and performance monitoring can contribute to more predictable aircraft turnarounds, helping ground operations align with airline efforts to reduce costs, emissions and operational variability.