- Problem
- A major U.S. airline experienced a catastrophic disruption that resulted in over $500M in operational losses, driven largely by the inability to efficiently recover crew schedules during irregular operations. We were brought in to define a technology strategy and develop an AI-based optimization tool to future-proof the airline's day-of-operations response.
- Action
- Conducted a detailed analysis of the airline's crew recovery pain points and defined a roadmap for an AI-powered solution that would optimize reserve usage, reroutes, and deadheads within labor and operational constraints. Led cross-functional execution across engineering, data science, and flight ops teams to translate this strategy into a production-ready tool, ensuring real-time performance, alignment with labor rules, and seamless integration into day-of-operations control centers.
- Result
- Successfully deployed the platform into day-of-operations control centers, reducing manual triage, accelerating recovery timelines, and materially improving operational resilience—setting a new standard for how the airline manages crew disruptions under stress.