NDA first. Before discovery, before access, before detail.
Confidentiality starts at step one, not after back-and-forth. We begin under NDA before product architecture, customer data patterns, incident history, or roadmap specifics are shared.
Security & Compliance
Move faster with QA—without loosening your security standards.
If a QA partner needs broad access, vague AI policies, or trust-by-PDF, that is not a partner. Every AQA Masters engagement starts under NDA, then runs through scoped permissions, approved tooling, governed AI usage, and reviewable evidence—so you gain release confidence without expanding exposure.
Security principle
14-Day AI-Augmented QA Pilot Pass
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for the AQA Masters quality model
Minimum necessary access. Maximum decision-grade evidence.
Security is not a slide deck claim. It is a working model: who gets access, to what, for how long, under which controls, and with what review trail. That is how we protect your environment while improving release decisions.
Security operating model
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We earn access in layers, prove controls in writing, and keep ownership with your team.
You do not need a vendor who asks for everything. You need a system that gets signal with the minimum safe exposure. We run QA through explicit boundaries, approval gates, and artifacts your security and compliance teams can inspect.
Scoped access approved by your owners, not ours.
Permissions are bounded to the engagement objective and granted through your process. We work with client-approved tools and least-privilege visibility instead of asking for broad, persistent access.
Data and credential boundaries are explicit and enforced.
Secrets, tokens, logs, customer records, and production-like environments follow your controls. If masked data, sanitized payloads, or read-only access are the safe path, that becomes the default operating mode.
AI is governed by policy, review, and human accountability.
AI supports speed where appropriate—analysis, test design acceleration, and reporting—but governed by rules your team approves. Sensitive data and credentials stay out of AI workflows unless explicitly authorized.
Every security-relevant decision leaves a reviewable trail.
Risk findings, coverage intent, release criteria, and recommendations are documented so engineering, product, security, and compliance stakeholders can audit what changed and why.
You own the system, assets, and know-how.
Test suites, prompts, playbooks, operating rules, and release criteria are built for your team to keep. No black box, no lock-in mechanics, no hidden dependency model.
FAQ / objections
The questions responsible teams ask before giving QA access.
Clear answers on NDA timing, access scope, data boundaries, AI governance, auditability, ownership, and how to validate fit in a controlled 14-Day AI-Augmented QA Pilot.
NDA-covered
Scoped access
Data handling
AI governance
Yes. NDA is the starting line, not a later checkpoint. We do not ask for sensitive architecture, customer, or release details before confidentiality is in place.
No. Full access is usually a risk smell, not a requirement. We start with scoped, client-approved permissions and expand only when the work and your owners justify it.
By operating inside your controls: least-privilege access, approved tools, and explicit handling rules for logs, secrets, and customer data. If sanitized datasets or restricted visibility reduce risk, we use them by default.
AI usage is human-governed and policy-bound. It accelerates QA workflows where allowed, but sensitive data, credentials, and restricted information stay out unless your team explicitly authorizes a controlled process.
Yes. We produce reviewable artifacts that map to your internal expectations—what access was used, what was tested, what risk was found, and what release recommendation was made.
You do. The assets, frameworks, and release criteria are built as client-owned property so your capability compounds after the engagement instead of resetting every quarter.
Because trust should be proven, not assumed. In 14 days, you can validate how we operate under NDA, inside your controls, with your security boundaries—before expanding scope.
Want confidence without increasing exposure?
Book a Fit Call.
Use the pilot to evaluate our security posture in practice: NDA-first onboarding, scoped permissions, governed AI usage, and reviewable QA evidence your stakeholders can trust.
NDA before access
Least-privilege scope
Every asset stays yours
No long-term lock-in
Your call host
Horia Adamov
QA Architect