Accessibility testing that sees like a human.
Two analysis engines run on every scan — automated WCAG rule checks plus GPT-4o visual reasoning over a real screenshot. Catch what scanners alone can't see.
- Powered by GPT-4o Vision · OpenAI
- axe-core engine · Industry standard
- WCAG 2.2 criteria · Full coverage
- Real screenshot · Not a simulation
- Two analysis layers · Rules + AI vision
- Zero data stored · Scan, read, done
How it works
Two engines, one report
Paste a URL. Both engines run automatically and the results arrive together.
Automated WCAG Analysis
axe-core runs against the live DOM and flags structural violations — missing alt text, ARIA misuse, landmark issues, invalid semantics — mapped to exact WCAG 2.2 success criteria.
Visual AI Review
GPT-4o receives a full-page screenshot and reasons about what a human evaluator would notice: touch target sizing, visual hierarchy, color-only cues, and contrast over complex backgrounds.
Unified Intelligence
Both engines report to a single accessibility score with issues grouped by severity. Every finding includes a description, affected element, and a suggested fix.
Under the hood
What happens during a scan
Both engines run in parallel — results arrive in under 30 seconds.
- Navigating to URL
- Analyzing DOM structure
- Running WCAG rule checks
- Capturing full-page screenshot
- Sending to GPT-4o Vision
- Generating accessibility report
The report
Every scan delivers a full picture
A sample of what your accessibility report looks like — score, severity breakdown, and per-issue fix guidance.
Sample report · example.com
Accessibility Score: 62 / 100
26 issues found across 2 analysis engines
3
Critical
7
Serious
12
Moderate
4
Minor
Image missing alt attribute
7 <img> elements have no alt text — screen readers will skip them.
Insufficient touch target size
Primary CTA button is 28×28 px — WCAG 2.5.5 requires 44×44 px minimum.
Heading order skips level
<h1> followed directly by <h3> — assistive tech users lose document structure.
+ 23 more issues in the full report
AI Vision layer
AI sees what rules can't
A real screenshot is sent to GPT-4o — not a description, the actual pixels. It reasons about the visual experience the way a human evaluator would.
AI Vision finding
Touch target too small
Severity: Critical
The primary action button is 28×28 px. WCAG 2.5.5 requires at minimum 44×44 px for interactive controls.
Who is affected
Users with motor impairments, tremors, or those using touch devices with limited precision.
Suggested fix
Increase button dimensions to at least 44×44 px, or add min-h-[44px] min-w-[44px] with appropriate padding.
This kind of finding — measured from pixel dimensions in a real screenshot — cannot be produced by DOM-only rule-based scanners.
The gap
What rule-based scanners miss
Traditional scanners analyze the DOM. Aria analyzes the DOM and the visual experience.
Beyond automated rules
What Aria finds that others miss
The barriers that require visual reasoning — the kind only a human evaluator or a vision model can catch.
Visual hierarchy problems
Unclear reading order, buried CTAs, and structural confusion that disorients screen-magnifier and low-vision users — invisible to DOM scanners, visible in pixels.
Touch target sizing
Interactive elements measured from their rendered pixel dimensions. Rules can't know if a button's padding makes it large enough; GPT-4o can.
Cognitive complexity
Dense text walls, inconsistent layouts, and unpredictable patterns that raise the cognitive bar for users with ADHD, dyslexia, or processing differences.
Color as sole signal
Error states, status indicators, and data encoded only in color. Caught visually — both the element and the surrounding context matter.
Contrast over backgrounds
Text rendered over gradients, images, or layered colors where computed contrast ratios don't tell the full story. GPT-4o evaluates the actual composite.
Ambiguous interactive cues
Hover-dependent affordances, non-obvious clickable areas, and missing focus indicators that a DOM walk can't surface without seeing the rendered output.
Find what your scanner misses.
Paste any URL — no account required. Results arrive in under 30 seconds, combining automated WCAG checks with AI visual analysis.