Cutting Enterprise QE Costs by 10% for Airline Ops

Client

A major international airline running a large in-house Quality Engineering (QE) organization across a broad application portfolio.

Challenge

The airline’s enterprise QE covers the consumer flight-booking platform and agent-facing travel-desk apps, where regressions pose a risk to revenue and operations
Leadership mandated a ~10% QE budget cut via AI, without reducing coverage or slowing releases. The challenge was largely manual, labor-intensive testing that scaled costs linearly with delivery, and a locked MarsX / Azure DevOps (ADO) toolchain hindering automation

Solution

We adapted Test Author to plug directly into the existing MarsX / ADO environment and maintain test coverage across the booking and travel-desk surfaces.
Provided hands-on playground access to a real, working product
A dedicated Alpha Pod then executed the custom build, with a defined IP-transfer path so the airline ultimately owns the system outright.

Impact

Selected over competing solutions as the only candidate meeting the conditions to deliver the mandated ~10% QE budget cut (with no loss of test coverage or release velocity).
Decoupled testing cost from release volume by automating manual, labor-intensive regression work, recovering skilled QE capacity for higher-value testing.
Protected the revenue-critical flight-booking and travel-desk platforms with sustained full regression coverage.

Strategic Significance

Demonstrates Indexnine’s ability to use an AI-first approach to operationalize Indexnine SNAP^TM Test Author within a TMAP-aligned QE function, modernizing enterprise testing into a measurably leaner, automated practice.

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