Context first. Quality always.
From product context
to quality intelligence.
Understand the product. Challenge the gaps.
Make better quality decisions before shipping.
Q.uai brings requirements, project knowledge and engineering evidence into one connected quality workflow.
In development · contact the founder
A clearer view of quality
Before you test it,
understand it.
Good tests start with good questions. Bring the requirement closer to its business rules, challenge what is missing and review the evidence behind every recommendation.
- Context belongs to the project.Keep its requirements, knowledge and analyses together.
- Evidence before confidence.A citation makes the source inspectable. Judgment still matters.
- Recommendations you can review.You decide what to change, test or automate.
Order cancellation
One requirement. Its rules. The evidence behind the review.
When should the refund arrive?
The sample rules require a receipt, but do not specify a refund deadline.
Example requirement + project documentThe Q.uai approach
Understanding comes before generation.
A deliberate path from product knowledge to useful engineering action.
- 01
Understand
Start with requirements, business rules and project knowledge.
- 02
Challenge
Find ambiguities, missing criteria and questions worth asking.
- 03
Reason
Connect the finding to its evidence. Make uncertainty visible.
- 04
Recommend
Decide what to test and automate, with an engineer in control.
The platform we are building
Connected context.
Explainable decisions.
Explore the capabilities in private development and where Q.uai is going next. Public workspace access is not available yet.
Jira, GitHub and existing tests will enrich the same project context. These integrations are planned.
- 01Private preview
Project context
Requirements, versioned TXT, PDF, DOCX, CSV, Excel and XML documents, with source evidence scoped to each project.
- 02Private preview
Requirement intelligence
Advisory risks, open questions, test scenarios and automation opportunities.
- 03Planned
Repository-aware analysis
Bring Jira, GitHub code and existing tests into the same project context before proposing new coverage.
- 04Planned
Explainable Quality Brief
Bring product and engineering evidence into one reviewable brief, with future automation guidance for Playwright, Cypress, Robot Framework and Selenium.
- 05Later
Release intelligence
Connect changes, defects and quality signals as measured history grows, followed by data validation and AI quality/cost insights.
AI Quality Command Center
Build quality on understanding.
Start with your project. Bring the context. Ask better questions.