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.

Missing Structured Data Kills AI Citations | AiVIS Cite Ledger

Your content might be crawler-accessible, but without structured data, AI models have no reliable way to attribute, verify, or cite it. Structured data is the citation bridge.

What AI Models Need from Structured Data

JSON-LD schema tells AI models what your content is (Article, FAQ, Product), who wrote it (author), and when it was published. Without this, models guess, and often guess wrong.

Open Graph tags provide pre-formatted summaries that AI models use for quick content classification and display formatting.

Which Schema Types Matter Most

Article schema: essential for blog posts, news, and editorial content. Includes author, datePublished, headline, and description.

FAQ schema: tells AI models your page contains Q&A content, making it eligible for featured answer boxes and direct citations.

Organization schema: establishes your brand entity, connecting your content to a verified publisher identity.

Adding Structured Data to Your Site

Add JSON-LD in a <script type='application/ld+json'> tag in your page's <head>. Don't use Microdata or RDFa, JSON-LD is the format AI models prefer.

Test your schema output with Google's Rich Results Test and validate with an AiVIS Cite Ledger audit to ensure AI crawlers receive the markup correctly.

Frequently Asked Questions

Does structured data guarantee AI citations?: No, but it significantly increases the probability. Structured data makes your content machine-verifiable, which AI models prioritize when generating citations.
Which structured data format should I use?: JSON-LD. It's the format recommended by Google and preferred by AI models. Microdata and RDFa are harder to maintain and less reliably parsed.
How much structured data do I need?: At minimum: Organization, Article (for content pages), and FAQ (for Q&A content). Add Breadcrumb, Product, and HowTo where relevant.