Case study · Global Entertainment Enterprise
Cutting performance scripting cycles by more than half
A sprawling entertainment platform was drowning in manual load-test scripting. AI-enabled automation accelerators cut the cycle time by over 50% while raising execution quality.
- scripting cycle reduction
- >50%
- scripting cycle reduction
- execution quality & consistency
- Higher
- execution quality & consistency
- overall testing cost
- Lower
- overall testing cost
- release sign-off cadence
- Faster
- release sign-off cadence
The challenge
Every release train depended on a performance scripting backlog that grew faster than the team could clear it. Scripts were hand-built, correlation consumed engineer-days per transaction, and sign-offs kept slipping because test coverage lagged development.
The business needed a way to scale performance validation across a complex, integration-heavy landscape without linearly growing headcount — and without letting quality erode.
What we did
- 01
NFR discovery & scenario triage
We mapped critical business transactions against risk and usage data, then prioritized scenarios by business impact — so automation effort landed where it mattered first.
- 02
AI-accelerated script engineering
Our automation accelerators handled correlation, parameterization, and first-pass validation automatically, compressing work that took days into hours while engineers focused on scenario strategy.
- 03
Quality gates in the pipeline
Baseline comparisons and trend analytics were wired into Azure DevOps so regressions surfaced at build level instead of at release.
- 04
Enablement & handover
Internal engineers were trained on the accelerator workflow, making the speedup permanent rather than consultant-dependent.
More results
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