We start with the flows that matter.
Checkout, payments, onboarding, access, billing, data sync, or whatever your users depend on. We focus first where failure would hurt.
Who We Are
We make fast releases feel safe again.
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.
Company belief
14-Day AI-Augmented QA Pilot Pass
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Book a Fit Call
for the AQA Masters quality model
More QA activity is not the answer.
The answer is knowing what matters, what can break, what to automate first, where AI helps, and what your team needs before every release.
Why we exist
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Your team ships fast. Quality has to keep up.
More code, more changes, and more AI-assisted work are great until releases start feeling heavier than they should. AQA Masters helps you see what can break, protect the flows that matter, and build QA your team can keep using.
We make release risk visible.
Your team gets clear priorities: what is covered, what is missing, what should be automated, and what needs attention before shipping.
We use AI to move faster.
AI helps with test ideas, coverage review, bug context, flaky tests, reporting, and automation support — without turning QA into a black box.
You keep what gets built.
The code, workflows, findings, roadmap, and QA assets stay with your team. Built around your stack. No vendor lock-in.
Top Romanian QA talent. One AQA standard.
The standard is simple: understand the product, protect what matters, build useful automation, use AI with judgment, and keep QA tied to real release risk.
01 / Top QA talent
Cluj-Napoca, Romania
Selected for technical depth, automation discipline, and the ability to understand how modern product teams actually ship.
02 / One AQA standard
Bucharest, Romania
The same bar for every client: clear QA thinking, useful automation, AI-assisted execution, and release work tied to what actually matters.
FAQ / objections
The questions serious teams ask before trusting QA to an outside partner.
Short answers on why the model starts with leadership, how AI-Augmented QE continues the work, and why your team owns what gets built.
Model
AI governance
Team fit
Ownership
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.
Not an audit. Real implementation.
14 days. From QA gaps to shipped fixes.
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.
NDA before access
Least-privilege scope
Every asset stays yours
No long-term lock-in
Your call host
Horia Adamov
QA Architect