What exactly is AiVIS Cite Ledger?

AiVIS Cite Ledger is an evidence-backed AI citation audit and remediation system. It measures how AI models, ChatGPT, Perplexity, Claude, and Google AI, interpret, trust, and cite your web content. The result is a 0–100 CITE LEDGER score across seven weighted dimensions, with BRAG evidence-linked findings and prioritized fixes.

How is this different from Semrush, Ahrefs, or Clearscope?

Traditional SEO tools optimize for keyword ranking in traditional search results. AiVIS Cite Ledger audits citation readiness, the specific signals that determine whether AI answer engines retrieve and cite your content. A page can rank #1 on Google and be completely invisible to AI answer synthesis.

What is BRAG and how does it make findings trustworthy?

BRAG stands for Based-Retrieval-Auditable-Grading. It ties every audit finding to a real, traceable element on your page, a specific heading, schema block, meta tag, or content section, each carrying a unique evidence ID. You can open the element, verify the finding, and recheck it after a fix. No black boxes.

Is the free tier genuinely useful, or just a teaser?

The Observer (free) plan gives you a full composite CITE LEDGER score and all seven dimension letter grades, so you can see exactly where you stand and which categories are hurting you. BRAG evidence IDs and prioritized fix packs require a paid plan. Three audits per month, no credit card.

Framer AI Visibility Audit | AiVIS Cite Ledger

Framer produces beautiful interactive sites, but animations, transitions, and client-rendered content create AI visibility blind spots that most designers don't realize exist.

How Framer Renders for AI

Framer generates static HTML for published sites, which is good for AI crawlers. However, interactive components and animated sections may rely on JavaScript that crawlers skip.

Framer's CMS pages receive server-rendered output, but the quality of that output depends on how you've structured your content fields.

Framer AI Visibility Gaps

No built-in JSON-LD schema. Framer focuses on visual design and lacks structured data tools entirely.

Limited meta tag control: while you can set SEO titles and descriptions, Open Graph images and other tags require workarounds.

No robots.txt or llms.txt customization without deploying through a proxy or custom domain configuration.

Fixing Framer for AI

Use Framer's custom code injection to add JSON-LD schema in the page head. This requires writing schema manually for each page type.

Ensure all important text content is in static elements, not exclusively in animated or interactive components.

Run an AiVIS Cite Ledger audit to see what AI models actually receive when they crawl your Framer site, the visual output and the machine-readable output are often very different.

Frequently Asked Questions

Can AI models read Framer sites?: Framer generates static HTML for most content, so AI crawlers can read it. But interactive elements and animations may contain content that crawlers miss.
Does Framer support structured data?: Not natively. You need to inject JSON-LD via Framer's custom code feature, which requires writing schema markup manually.
Is Framer better than Webflow for AI visibility?: Webflow offers more control over custom code, meta tags, and structured data. Framer is catching up but currently requires more workarounds for AI visibility.