4 verified profiles
What clients valueAI-Augmented QA · Human QA judgment · Release confidence
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Top 1 Software Testing CompaniesBucharest, Romania
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Top 1 Software Testing CompaniesBucharest, Romania
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Published category scores5.00 across 4 categoriesBudget · Quality · Schedule · Communication
View profile (opens in a new tab)Architect-Led From Day One.
AQA Masters delivers AI-Augmented QA and software testing services by embedding QA leadership and ISTQB-certified, AI-augmented engineers into your product team so releases move faster with clearer risk, and smarter workflows.
We turn every sprint’s change into ranked flow risk, coverage direction, and an automation queue your team can execute.
We turn critical-path evidence into a release call your team can act on before release week.
AI drafts tests and finds signals. A QA Architect reviews the work, owns the decision, and keeps every approved workflow in your repository.
One managed quality system.
Architect. Lead. Embedded QE. AI-Augmented QE.
Most QA providers give you extra hands. AQA Masters gives you an Embedded QE who learns your product and drives day-to-day quality, backed by a shared QA Architect, QA Lead, and AI-Augmented QE team.
More testing does not make a release safer. Signal does. These case studies show how AQA Masters turns live data and cloud automation risk into coverage your team can trust before release day.
Live data flows protected
Critical API coverage for live scores, fixtures, standings, player stats, and high-volume data feeds.
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Bucharest, Romania
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Bucharest, Romania
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“AQA Masters does not treat QA like a checklist. They used AI in a practical way to create better test scenarios, check coverage faster, and support validation, while the final thinking still came from experienced QA engineers.”
“Their reliability, ownership, and QA expertise stood out. They understood our product needs quickly, identified the right areas to focus on, and used AI in a practical way while keeping experienced QA judgment in control.”
“They strengthened QA coverage across our critical flows and focused on release confidence rather than testing volume. AI made testing faster, while human review kept it grounded in user experience and business impact.”
“AQA Masters modernized our QA pipeline by automating critical testing workflows and benchmarking generative AI solutions against accuracy, reliability, and performance metrics.”
No. AQA Masters is not a traditional QA outsourcing vendor.
We install one managed quality system around your product: a QA Architect, QA Lead, named Embedded QE, and AI-Augmented QE working together.
The goal is simple: help you ship faster, understand risk earlier, and make safer release decisions.
No. AI can generate output. It cannot carry release accountability.
We use AI to compress cycle time: draft tests, triage noise, and accelerate analysis. Humans still own policy, risk calls, and ship/no-ship judgment.
Simple: AI works for the team. The team does not work for AI.
AI speeds up pattern detection, coverage drafting, and evidence prep. QA leadership decides what is valid, what is risky, and what gets into release gates.
No blind trust. Only reviewable signal.
We choose one battle worth winning, then build proof inside your real product.
After a fit call, we lock one scope, set access boundaries, and define the success signal. Days 1–2 expose where releases actually break: critical flows, risk paths, coverage gaps, and signal issues.
Days 3–10 install trusted QA signal through high-risk checks, AI-augmented workflows, and reusable assets. Days 11–14 give you findings, client-owned assets, and a 90-day path to continue, extend, scale, or stop.
Yes. Always.
Tests, workflows, docs, and roadmap stay with your team. We do not build dependency. We build capability.
It should reduce disruption, not create it.
We work inside your existing repos, CI flow, and product rituals. First we improve signal quality and ownership clarity, then we recommend deeper changes only if the evidence supports them.
Even better.
We do not replace product context. We amplify it. Your team keeps ownership while we add architecture, release governance, AI workflow design, and execution standards.
Then this is exactly where the model shines.
We install the first practical QA layer: critical-flow priorities, ownership model, release checks, and starter assets your team can run and evolve.
Not to start.
We begin with your stack and workflows. If tooling changes are needed, we tie them to measurable gain, not to preference or hype.
You decide from proof, not pressure.
Option 1: stop and keep the assets. Option 2: extend the same scope. Option 3: scale into a broader QA operating model with us as embedded leadership.
Teams wanting checkbox QA reports or low-cost test execution should skip this.
This is for teams that treat quality as a growth lever and want leadership-level ownership, strong signal, and compounding release confidence.
No platform pitch. No theater audit. We map critical flows, expose expensive risk, apply AI where it creates leverage, and leave assets your team owns.
High-risk journeys mapped first.
Breakpoints, owners, and blockers exposed.
AI speed with human-governed judgment.
Client-owned assets and a 90-day plan.
If there is no leverage, we say no. If there is, we lock one scope, set access boundaries, and define the success signal.
We turn customer journeys into risk maps: coverage gaps, brittle suites, ownership blind spots, and high-cost failure paths.
We harden high-risk checks, reduce noisy feedback, and build AI-augmented QA workflows inside your current stack.
You get findings, assets, and a 90-day execution path. Continue, extend, or stop without guesswork.
Your decisionContinue, extend, or stop.
Wrong fit? We tell you fast. Right fit? We lock scope and start.
