Fare Comparison
Airline fare intelligence platform comparing competitors' real-time fares, flight schedules, and seat availability for data-driven pricing
An airline fare intelligence platform that enables airlines to compare competitors' real time fares, flight schedules, and seat availability, providing data-driven pricing recommendations to maximize revenue and profitability. Integrated multiple GDS and NDC suppliers to aggregate and normalize competitor data, and engineered pricing-intelligence logic to help airlines optimize ticket pricing.
What it does
An airline fare intelligence platform. Airlines use it to see what competitors are charging in real time — fares, flight schedules, and seat availability — and get data-driven pricing recommendations from that picture.
My role
I designed and built the platform end to end, from the supplier integrations through to the React dashboard airlines actually work in.
The integration layer pulls from multiple GDS and NDC suppliers, each returning data in its own shape and updating constantly. A large part of the work was normalizing those feeds into something comparable. On top of that I engineered the pricing-intelligence logic that analyzes the aggregated market data and generates fare recommendations.
Why this stack
Hangfire drives the recurring collection jobs — competitor fares have to be pulled continuously, not on demand, so the dashboard reads from data that is already there. EF Core rather than Dapper here, because this is a write-heavy aggregation workload where schema modelling matters more than raw read latency. PostgreSQL stores the normalized fare history that the comparison logic runs against.