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.

What Makes a Website Visible to AI Search | AiVIS Cite Ledger

AI search visibility is not the same as Google search visibility. The signals are different. This is the complete picture.

The ten scoring families AI search evaluates (the scoring model)

1. Schema & Structured Data (18%): JSON-LD presence to declare entity identity and content type. Hard blocker if absent.

2. Entity & Heading Signals (14%): Single H1 (hard blocker if absent), heading hierarchy, entity declaration clarity.

3. Authority & E-E-A-T (12%): Knowledge Graph record, SERP presence, external citations on-page.

4. Meta Tags & Open Graph (10%): Title tag (hard blocker if absent), meta description, OG tags, HTML lang.

5. Content Depth (10%): Word count ≥ 300, question-style H2s for snippet eligibility, TL;DR block.

6. Crawlability & Bot Access (8%): AI crawlers not blocked in robots.txt (hard blocker if blocked), llms.txt file.

7. Renderability & Page Speed (8%): Page load under 3 s, LCP under 2500 ms, image alt coverage.

8. Citation Signal Quality (8%): Meta description length 25–160 chars, meta/OG consistency, TL;DR position.

9. Indexability & Link Graph (6%): Canonical URL, internal links, external links, XML sitemap.

10. Security & Trust Signals (6%): HTTPS canonical, hreflang, zero evidence contradictions.

What Google visibility does and doesn't transfer

Technical SEO overlap: HTTPS, canonical URLs, page speed, and proper HTML structure benefit both Google and AI visibility.

Does not transfer: backlinks, keyword density, domain authority, social signals. These Google signals have no direct equivalent in the AI extraction pipeline.

New requirements: crawler allowances for AI bots (robots.txt), JSON-LD entity schema, and server-side rendering or pre-rendering for client-heavy sites.

Frequently Asked Questions

Is AI search visibility the same for all AI tools?: The core requirements are shared (crawler access, schema, rendering), but different tools weight context differently. ChatGPT's browsing favors recency, Perplexity favors citation-dense content, and Google AI Overview favors structured Q&A markup.
How is AI search visibility measured?: The audit measures it across ten scoring families, producing a composite 0-100 score with evidence IDs tracing each dimension to crawl observations.