AI-Powered Analysis

Revanote runs two parallel Claude AI calls every time you trigger a review — one using vision to spot visual and design problems, and one analyzing HTML to catch accessibility, SEO, and content issues. Both sets of findings are merged and scored, giving you a complete picture in seconds.

How it works

1. Visual analysis — Claude’s vision model examines the full-page screenshot for layout problems, poor contrast, unclear visual hierarchy, inconsistent spacing, and design issues that hurt user experience.
2. Semantic analysis — A second Claude call reads the page HTML and metadata to flag missing alt text, heading structure issues, broken ARIA roles, thin content, missing meta descriptions, and more.
3. Merged findings — Both result sets are combined and scored across four categories: Design, Accessibility, SEO, and Content.

What gets analyzed

Design issues

• Visual contrast and color accessibility
• Unclear call-to-action hierarchy
• Inconsistent spacing and alignment
• Mobile layout problems
• Typography legibility issues

Accessibility issues

• Missing or empty alt text on images
• Incorrect heading hierarchy
• Missing ARIA labels on interactive elements
• Form inputs without associated labels

SEO issues

• Missing or duplicate title tags
• Missing meta descriptions
• Thin or duplicate content
• Missing structured data opportunities

Content issues

• Vague or generic CTAs
• Inconsistent brand voice
• Readability score problems
• Missing trust signals

Why dual-model analysis matters

Single-pass AI tools either look at the screenshot or the HTML — not both. Revanote does both, so you never get a partial picture.