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.

Building Author Authority for Citation Workflows - E-E-A-T in the AI Era | AiVIS Cite Ledger Blogs

By R. Mason · 2026-03-11 · 10 min read · EEAT

AI systems are trained to prioritize authoritative voices. Here\

Key Takeaways

AI systems crawl Author.about, social profiles, and byline metadata to assess authority.
E-E-A-T signals (expertise, experience, authoritativeness, trustworthiness) now filter citation eligibility.
Your author contact info and verified credentials must be machine-readable (schema).
Companies without clear author attribution consistently show lower citation rates in LLM outputs - a pattern verified through AiVIS Cite Ledger citation testing across multiple AI answer engines.