Airlines are making significant progress in the shift from static, rule-based pricing towards continuous, dynamic revenue optimisation. What was historically too big a leap to take, given the complex technology and ecosystems involved, is now achievable by plugging in modern technology that works within those constraints. Existing infrastructure doesn’t need to be dismantled in favour of a full-scale system replacement, opening the door for airlines to begin their journey towards the industry’s ambition of more flexible pricing.

Datalex Pricing AI is a dynamic pricing solution built for exactly that transition — delivering revenue uplift while leaving the airline firmly in control of how, where and when it is applied.

Airline Control at Every Step

Airline control is fundamental to Datalex Pricing AI. A no-code configuration dashboard gives airlines control over where, how and when to apply dynamic pricing, so Revenue Management teams remain fully in charge while monitoring performance in real time.

Robust guardrails, defined by the airline, limit the extent of any price adjustment, and self-service A/B testing allows performance to be tracked on an ongoing basis. By automating time-intensive execution, Pricing AI frees Revenue Management teams to focus on strategy rather than manual tasks.

Intelligent route orchestration and real-time dashboards further strengthen human oversight and intervention, giving teams clear visibility into the impact of every pricing decision. This oversight is critical to optimising pricing at scale: Pricing and Revenue Managers can override recommendations, adjust parameters, or switch capabilities on and off at any time — with every pricing decision fully traceable and auditable.

Not every route has the same commercial goal, and Pricing AI is built to reflect that. Airlines can tune the solution to prioritise revenue uplift, load factor, or a defined balance between the two:  route by route, or across the network. Where filling seats matters more than yield, the airline can weight optimisation towards load factor; where yield is the priority, it can weight towards revenue.

This gives airlines a further layer of control, aligning automated pricing directly with their own commercial strategy rather than a single fixed objective.

Proven
Revenue
Uplift

Datalex Pricing AI is running in live production delivering a consistent 3–5% revenue increase across routes, with load factors and conversion holding steady or improving.

Some individual routes have seen uplift beyond 5%, driven by stronger demand dynamics.

Initial deployment takes approximately 12 weeks and can scale quickly across large numbers of routes.

Looking Ahead:
Bring Your Own Science

Building on this momentum, Datalex has developed Bring Your Own Science (BYOS), a new capability enabling airlines to integrate their own proprietary models and forecasting algorithms directly into Pricing AI. This reinforces Datalex’s commitment to openness, giving airline partners the freedom and flexibility to use their own models alongside Datalex’s proven capabilities to create a truly differentiated pricing experience.