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 ten weighted families (avs-v3), 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 ten family scores (avs-v3), 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.

Cited in ChatGPT But Not Claude, Perplexity, or Gemini? Here's Why | AiVIS Cite Ledger Blogs

By Founder, AiVIS Cite Ledger · 2026-06-25 · 11 min read · VISIBILITY-SYSTEMS

Your competitors show up in Perplexity answers. You show up in ChatGPT. Neither of you shows up in Claude. This is not luck — it is infrastructure.

Key Takeaways

Cross-model citation gaps are not random — ChatGPT, Claude, Perplexity, and Gemini each use different retrieval indexes and citation criteria.
ChatGPT sources via Bing (weights domain authority and backlinks); Claude uses its own index (weights entity clarity and authorship); Perplexity runs real-time crawls.
Being cited by one model but ignored by others reveals which signals are strong (causing that one citation) and which are missing (causing the gaps).
Full-spectrum citation requires Organization schema with sameAs links, author EEAT signals, fresh direct-answer content, and broad external web presence simultaneously.
AiVIS.biz audits show per-engine citation presence so you can diagnose and fix cross-model gaps rather than optimizing blindly for one model.

Article

# Cited in ChatGPT But Not Claude, Perplexity, or Gemini? Here's Why

The Asymmetry Is Not Random

If you are being cited by one AI model and ignored by three others, you have a cross-model citation gap. This is one of the most common patterns in AI visibility audits and one of the most misunderstood.

The instinct is to assume it is random — that AI models just happen to pick different sources. That instinct is wrong.

Cross-model citation gaps are structural. They reveal specific, identifiable differences in how each model's retrieval system evaluates your site. Understanding those differences is the path to closing the gap.

Why Each Model Cites Differently

**ChatGPT (OpenAI)**

ChatGPT draws on a combination of training data and live web retrieval via Bing integration. Sites with strong Bing search presence — high DA, consistent backlink profiles, well-structured crawlable content — tend to appear in ChatGPT answers for informational queries.

ChatGPT also weight sources that have been mentioned frequently in its training data. Older, more established sites with broad web presence often outperform newer but better-structured sites here.

**Claude (Anthropic)**

Claude uses its own index and does not use Bing. Claude places higher weight on clear entity declarations, explicit authorship signals, and content that reads as authoritative rather than promotional.

A site that is being cited by ChatGPT but not Claude typically has strong Bing presence but weak entity and authorship signals — the kind of signals Claude weights more heavily.

**Perplexity**

Perplexity runs real-time retrieval on every query. It is one of the most citation-transparent AI systems — users can see the sources it is pulling from. Perplexity weights content freshness, direct answer relevance, and structured data more heavily than other models.

Appearing in Perplexity requires content that directly answers the query within the first 200 words, is recently updated, and has schema marku

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