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Case studies · Hospitality & travel

Invoice-to-booking reconciliation for a travel retailer

Around 500 bookings a day produced 1,000 to 2,000 supplier documents, each checked against the booking by hand. An AI extraction and matching pipeline now surfaces only the discrepancies.

Client
A cruise and package-holiday retailer
Built with
Azure Data Lake, Azure Data Factory, Microsoft Fabric, Azure OpenAI, Power BI
Timeline
Eight months from discovery to phased rollout

The problem

Supplier invoices, tickets and certificates arrived in every format the travel industry uses, and a team verified each one against the booking manually. Errors slipped through, revenue leaked when supplier invoices did not match bookings, and amendments made by customers after a booking were often not passed to suppliers.

What we built

  1. 1A central data platform on Azure with pipelines from the booking system and the CRM
  2. 2AI document extraction with a model trained on travel invoices and tickets, capturing passengers, itineraries, flights and pricing
  3. 3Matching rules comparing extracted data with booking records and flagging discrepancies
  4. 4Amendment tracking to confirm every booking change reached the supplier
  5. 5Dashboards for reconciliation status and exceptions

What changed

  • —Reconciliation moved from reading every document to reviewing a queue of exceptions
  • —Amendment gaps between bookings and suppliers became visible instead of discovered by the customer

This project became a ready-made offer you can start from.

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