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.

The SSFR Evidence Framework: The Scoring Engine Behind Every AiVIS Cite Ledger Audit | AiVIS Cite Ledger Blogs

By R. Mason · 2026-03-24 · 7 min read · TECHNOLOGY

Before the AI scores your page, 27 deterministic rules have already decided how much of your content is actually extractable. Here is how SSFR works.

Key Takeaways

SSFR evaluates 27 deterministic rules across four categories: Source, Signal, Fact, and Relationship evidence.
Source evidence verifies content authorship and entity traceability for AI citation confidence.
Fact evidence measures verifiable claim density. AI models cite specific, measurable content over vague assertions.
Relationship evidence maps how content connects to the broader web through links, citations, schema, and entity consistency.
Every audit recommendation traces back to a specific SSFR rule, not a heuristic or opinion.

Article

When you look at a web page, you see content. When an AI model looks at a web page, it sees evidence. Or the absence of it.

The SSFR framework is the deterministic scoring engine that runs before any AI model evaluates your page in an AiVIS Cite Ledger audit. It answers one question: how much of this page's content is actually machine-extractable and trustworthy?

SSFR stands for Source, Signal, Fact, Relationship. These are the four categories of evidence that AI answer engines evaluate when deciding whether to cite a source; 27 rules across four categories. No opinions. No model randomness. Deterministic pass-or-fail evaluation.

Source Evidence

Source evidence answers the question: who created this content and can the identity be verified?

The rules in this category check for:

**Organization schema.** Does the page have a JSON-LD Organization block identifying the entity behind the content? AI models use this to associate content with a known entity.
**Author entity.** Is there a Person schema with name, role, and credentials? Pages with verified author entities get cited at higher rates than anonymous content.
**Publication date.** Is the content dated in both visible text and structured data? AI models use freshness signals to determine relevance. Undated content gets deprioritized.
**Canonical URL.** Is there a canonical tag pointing to the authoritative version of the page? Duplicate content without canonicalization confuses retrieval systems.
**Publisher identity.** Does the schema connect the article to a publisher entity with verifiable attributes?

Each source evidence rule produces a pass, partial, or fail. A page with complete source evidence is a page that AI models can trace back to a known, credible entity. That traceability directly affects citation probability.

Signal Evidence

Signal evidence covers the technical indicators that AI platforms use as trust proxies.

**HTTPS.** Not optional. Every AI platform downgrades or igno

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