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.

Organization Schema: The Minimum Viable JSON-LD Block That Unlocks AI Citation | AiVIS Cite Ledger Blogs

By R. Mason · 2026-06-04 · 8 min read · SEO

If an AI cannot tell who is behind your content, it will not quote you. Organization schema with the right sameAs links is how you become an attributable entity.

Key Takeaways

Pages without Organization schema have 60–80% lower AI citation probability, anonymous content is unquotable.
sameAs is the real unlock: it resolves your entity across AI training data.
Pages with 3+ sameAs links have 2.4x higher citation probability for branded queries.
Highest-weight sameAs targets: Wikidata/Wikipedia, Crunchbase, LinkedIn, GitHub, canonical URLs only.
Back schema with a clear About page; its absence averages 40% lower entity-clarity score.

Article

Missing Organization schema is one of the most common hard blockers we find. Pages without it have a 60–80% lower citation probability in AI answer synthesis, because the model literally cannot attribute the content to a known entity. To an answer engine, anonymous content is unquotable content.

The fix is small and high-leverage. Here is the minimum viable block and the part most people get wrong.

The minimum viable Organization block

Put this in a script tag of type application/ld+json in the head:

{

"@context": "https://schema.org",

"@type": "Organization",

"name": "Your Company",

"url": "https://example.com",

"logo": {

"@type": "ImageObject",

"url": "https://example.com/logo.png",

"width": 512,

"height": 512

"sameAs": [

"https://www.linkedin.com/company/your-company",

"https://en.wikipedia.org/wiki/Your_Company",

"https://www.crunchbase.com/organization/your-company"

]

}

Required: type, name, url, logo. The field that actually moves citation is sameAs.

Why sameAs is the real unlock

sameAs is the primary mechanism AI systems use to resolve your identity across their training data, it ties "Your Company" on your site to the same entity on Wikipedia, Wikidata, LinkedIn, or Crunchbase. Without it, the entity is treated as unverified and local, and it cannot be referenced across queries.

The number worth remembering: in our ledger, pages with 3+ sameAs links have a 2.4x higher citation probability for branded queries. Three is the practical threshold. One LinkedIn URL is better than nothing, but it does not anchor you to the knowledge graph the way a Wikipedia/Wikidata/Crunchbase trio does.

Which sameAs links actually matter

In rough order of weight for entity resolution:

1. Wikidata and Wikipedia, the backbone of most knowledge graphs.

2. Crunchbase, strong for companies and funding entities.

3. LinkedIn company page, widely cross-re

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