Design QA for AI-generated interfaces
AI builders move fast. The output often drifts — spacing breaks, hierarchy weakens, components go inconsistent. AIDQA runs automated design checks and tells you exactly what to fix.
AI builders can generate a screen in seconds. But the output usually lands in a dangerous middle zone: looks almost right, but something feels off.
Spacing drifts between sections
Hierarchy collapses under secondary content
Components that should look the same don't
Accessibility risks appear quietly
Design debt compounds with every iteration
Experienced designers catch this quickly. Most builders don't — and the cost is design debt that compounds with every iteration.
AIDQA is not a screenshot diff tool. It doesn't require a baseline. It inspects your interface against internal consistency, design rules, and accessibility thresholds — then returns prioritized findings with evidence and repair guidance.
Design QA for AI-generated interfaces means:
No baseline required inspects internal consistency, design rules, and accessibility thresholds — works on screen one of a project
Prioritized findings with evidence each issue includes an evidence region, explanation of impact, and concrete repair guidance
The step most teams skip Idea → AI generation → Design QA → Refinement → Production. AIDQA is the QA layer that fits fast workflows
Submit → Inspect → Fix. No setup required.
Upload a PNG, JPG, or paste a public URL. AIDQA renders a normalized frame and extracts structural metadata.
The rule engine checks layout, hierarchy, consistency, accessibility, and design-system patterns. No baseline required.
You receive 3–7 findings ranked by severity, each with an evidence region, explanation of impact, and concrete repair guidance.
AIDQA runs automated design QA for AI-generated interfaces across three dimensions:
Layout & spacing
Flags rhythm breaks, edge misalignment, and whitespace imbalance. Every spacing gap that doesn't fit the dominant scale gets surfaced.
Hierarchy & consistency
Detects weak primary actions, heading scale failures, button style drift, and card component variance. Finds where repeated elements stopped being consistent.
Accessibility risk
Catches text contrast failures below WCAG AA (4.5:1), touch targets smaller than 44×44px, and missing state coverage before they reach users.
Because one "looks broken" moment can cost more than the tool.
Catch layout drift and broken interactive patterns before they cost conversions.
Replace manual visual checks with a structured scan and a prioritized fix list.
A product can function correctly but still feel unreliable. AIDQA catches the gap.
Surface contrast failures below WCAG AA and touch targets below 44×44px before handoff.
Fewer missed issues, fewer regressions, fewer post-ship corrections.
One prevented broken release pays for AIDQA.
Indie hackers and solo builders using v0, Lovable, or Cursor — who can tell the output is weak but can't diagnose why.
Startup product teams generating UI quickly without strong design review — who need guidance before handoff, not governance after the fact.
Frontend and design engineers who want objective signals before a pull request ships a visual regression.
Design systems teams who need consistency enforcement without manual audits on every generated screen.
Submit a URL or screenshot. Get prioritized findings with evidence regions and repair guidance — no setup required.
AIDQA is the design QA layer that catches what AI builders miss — before your users feel it.
Get early access to the scanner, sample reports, and priority onboarding.
No spam. Limited early slots. We'll email you when your invite is ready.