Flight Routing AI

Overview

Led delivery of an AI solution to optimise routing decisions, balancing performance gains with safety and regulatory requiremen ts. Worked alongside operational and engineering teams to ensure outputs were practical and trusted.

Business problem

• Complex routing decisions needed to account for operational, safety, and regulatory constraints without sacrificing performan ce.
• Teams required confidence in model outputs before adopting them in production workflows.
• Stakeholders wanted measurable improvements while protecting safety and compliance obligations.

Approach

• Developed models incorporating operational rules, constraints, and historical performance data to guide recommendations.
• Established testing, simulation, and validation processes with domain experts to stress-test edge cases.
• Built change management, documentation, and training so teams could interpret and challenge AI outputs safely.
• Set up monitoring and feedback loops to refine the models as operating conditions changed.

Outcome

• Optimised routing recommendations aligned with safety and regulatory expectations.
• Teams trusted the solution through transparent validation, documentation, and shared simulations.
• Clear metrics demonstrated performance improvements and informed ongoing tuning.