What if an airline could identify ten additional weekly flights without adding a single aircraft to its fleet?
That is the scheduling opportunity identified by Optifly’s Opty, an agentic artificial intelligence system designed to help airlines explore complex network scenarios, optimise aircraft utilisation and evaluate commercial opportunities through automated analysis.
The technology combines natural-language interaction and AI agents with Optifly’s existing mathematical optimisation engines, covering airline scheduling, slot management, fleet allocation and network planning.
Moving Beyond Traditional Schedule Optimisation
Airline scheduling requires balancing aircraft availability, airport slots, passenger demand, operating constraints and commercial performance.
Opty allows planners to interact with scheduling information using natural language.
Airlines already use Opty in production to analyse and explain schedules, make changes and work with Optifly’s optimisation technology.
However, its more advanced agentic capabilities are scheduled for rollout beginning in January 2027.
AI Agents Exploring Scheduling Scenarios
The upcoming functionality will allow planners to describe scheduling challenges directly to Opty.
For example, an airline could request a 10% reduction in winter capacity while protecting profitability and maintaining frequencies on strategically important routes.
AI agents would coordinate Optifly’s optimisation engines to generate and compare dozens of alternative schedules, considering demand, bookings, commercial performance, operating rules and airport slot utilisation.
Proposed changes would be checked against airline constraints using Optifly’s optimisation and validation engines, with final approval remaining with the scheduler.
Identifying Additional Revenue Opportunities
Optifly reports that Opty identified opportunities for ten additional weekly flights within an already optimised summer schedule, using the same aircraft fleet.
The company estimates these additional services represented up to €6 million in potential revenue.
This represents a company-reported revenue opportunity, not independently verified realised revenue.
Optifly also reports that its established optimisation technology has delivered aircraft utilisation improvements of up to 5% and fuel-burn reductions of 0.3–1.0% through improved aircraft allocation.
These historical results should not be attributed exclusively to Opty’s new AI capabilities.
Why This Matters for Flight Operations
Opty illustrates how agentic AI could shift airline planning from manually testing individual scenarios to evaluating multiple alternatives through automated workflows.
The distinction is significant: AI interprets planning objectives and coordinates the analysis, while mathematical optimisation validates proposed solutions.
For airlines, the potential benefit is faster planning decisions without removing human control over operational and commercial constraints.
