Real projects, real problems, measurable results. Client names are withheld under NDA — the numbers are ours to stand behind.
Real estate: from QA bottleneck to predictable releases
The client: a real-estate platform where listings, search, and lead flows drive the entire business — every broken form is a lost buyer.
The problem: the development team was moving fast, but quality wasn’t keeping up. Developers tested their own code, there was no test plan and no regression process, and QA had become the bottleneck of every sprint: features queued for days waiting on manual checks, and bugs still reached production. A legacy front-end made every change riskier than it looked.
What we did: embedded a QA team through our A.R.R.A.Y. method — starting with an analysis that mapped the product’s critical flows into a documented test suite. We introduced risk-based testing so critical listing and lead flows got the deepest coverage, automated the regression pass for core journeys, and wired it into the CI/CD pipeline so every change was verified before merge. During the client’s migration to a modern front-end stack, the automated suite acted as the safety net that kept the rebuild from breaking what already worked.
The result: the full regression pass went from days of manual work to an automated run measured in minutes, releases stopped queuing behind QA, and critical-flow bugs were caught before deploy instead of after. The QA process scaled with the roadmap instead of blocking it.
Services used: QA outsourcing · test automation
iGaming: quality at the speed of live betting
The client: an iGaming operator whose platform settles real-money bets in real time. In this industry a defect isn’t a ticket — it’s money moving the wrong way, 24/7, on live sporting events that won’t pause for a hotfix.
The problem: a rapid release cadence with no dedicated quality gate. Odds display, bet placement, and settlement logic changed weekly; regressions surfaced in production, and the support team drowned in incident tickets with no knowledge base and no structured triage between support levels. Every launch weekend was a fire drill.
What we did: deployed a dedicated QA team working in the client’s time zone and tools. We built automated coverage for the money paths first — bet placement, odds updates, settlement, and payments — running on every release candidate, plus targeted load testing ahead of major sporting events. On the support side we introduced structured L1/L2/L3 triage, a knowledge base of known issues and resolutions, and reproduction of production incidents in lower environments so fixes were verified before redeploy.
The result: settlement and payment defects were caught pre-release instead of in production, incident volume fell as recurring issues were documented and eliminated at the source, and the operator kept its fast release cadence — now with a quality gate in front of real money instead of behind it.
Services used: dedicated QA team · test automation · application support
What both stories have in common
- Analysis before action — we map the product’s critical flows before writing a single test
- Risk-based coverage — the flows that cost money when they break get tested hardest
- Automation as a safety net — regression runs on every change, not the week before release
- Knowledge you keep — test suites, documentation, and processes stay with you, not with us
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