Cluj-Napoca, Romania
Selected for technical depth, automation discipline, and the ability to understand how modern product teams actually ship.
We build AI-Augmented QA systems around the flows that can hurt the business if they break. Architect-led. Human-governed. Built inside your stack.
Short answers on why the model starts with leadership, how AI-Augmented QE continues the work, and why your team owns what gets built.
Both, but not in the usual order. We start as your QA leadership layer: release risk, critical flows, automation direction, and decision signals. Then we add AI-Augmented QE on the project where execution creates leverage.
No. We make the team you already have sharper where it counts. Leadership gives the system direction. AI-Augmented QE adds focused execution. Your team keeps the context, the assets, and the ownership.
AI does not get to declare quality. It accelerates analysis, test design, automation support, and reporting. Senior QA judgment decides what is trusted, what gets reviewed, and what can influence a release decision.
Yes. Test assets, findings, prompts, automation improvements, QA guidance, and operating recommendations are built for your team to keep using. No black box. No forced dependency.
Because you should see the model work before committing bigger. In 14 days, we work inside your real product, expose the highest-value risks, and show whether a QA Architect, QA Lead, AI-Augmented QE, or a connected capability mix creates useful signal.
We implement AI-augmented QA, automated tests, and CI/CD quality gates inside your product. You keep every working asset—and see what we can ship before you scale us.
QA Architect