What is AI search visibility and why does it matter?

AI search visibility is the degree to which an AI system; such as ChatGPT, Perplexity, Claude or Google Gemini Overviews; can parse, trust and cite your website content in generated answers. A page that scores poorly for AI search visibility is unlikely to appear as a source or citation in AI generated responses, regardless of its traditional search ranking. AI search visibility depends on structured data quality, heading clarity, content depth, metadata completeness and machine readable formatting.

How does AiVIS.biz calculate a search visibility score?

AiVIS.biz runs a multi-stage audit pipeline: it crawls the target URL with a real browser, extracts structural signals (headings, schema, meta tags, body content, links), runs technical checks, then passes the evidence to a primary AI model for scoring. On Signal and Score Fix tiers, a second AI model peer-critiques the findings and a third validates the final result. The 0-100 CITE LEDGER score is a weighted composite across seven dimensions: Schema and Structured Data (20%), Content Depth (18%), Technical Trust (15%), Meta Tags and Open Graph (15%), AI Readability (12%), Heading Structure (10%), and Security and Trust (10%). Each finding is tied back to real page evidence.

What is the difference between AiVIS.biz and traditional query and answer engine tools?

Traditional SEO tools optimize for search engine crawlers and ranking signals like backlinks or keyword density. AiVIS.biz focuses specifically on answer engine readiness; whether AI systems can extract, trust and cite your content in generated responses. AiVIS.biz evaluates machine readability, entity clarity, schema coverage and citability rather than link authority. Every recommendation is evidence-linked, meaning it references the specific crawled signal that triggered it, not a generic checklist. The platform also tracks brand presence across citation sources and discussion platforms: Answer Engine Optimization (AEO).

What sources does brand mention tracking monitor?

Brand mention tracking scans 19 public sources: Reddit, Hacker News, Mastodon, DuckDuckGo site search, Bing site search, Google News RSS, GitHub repositories, Quora, Product Hunt, Stack Overflow, Wikipedia, Dev.to, Medium, YouTube, Lobsters, Bluesky, Twitter/X, Lemmy and GitHub Discussions. Available on the Alignment tier and above.

What plans does AiVIS.biz offer and what is included?

AiVIS.biz offers five tiers. Observer (free) includes 3 scans per month powered by open-weight AI models. Starter ($15/month) includes 15 scans per month with full recommendations, implementation code, PDF exports, and shareable links. Alignment (Core, $49/month) includes 60 scans per month with paid AI models, competitor tracking, brand mention scanning, reverse engineering tools, and WebMCP access. Signal (Pro, $149/month) includes 200 scans per month with a triple-check pipeline, citation testing, niche ranking, scheduled citation tests, team workspaces with 25 seats, full MCP/API access, and white-label reports. Score Fix (AutoFix PR, $299 one-time) uses higher capacity models and generates automated GitHub PRs with 250 credits.

AiVIS.biz | AI Visibility Audit — Evidence-Linked Scores

AiVIS.biz analyzes whether AI systems like ChatGPT, Perplexity AI, Google AI Overviews, and Claude can correctly read, interpret, and cite your website. Every result is tied to real on-page evidence, not assumptions.

TLDR

AiVIS.biz is the CITE LEDGER for AI answers. It audits how AI answer engines — ChatGPT, Perplexity, Claude, and Google AI — read, trust, and cite your website. Enter any URL to get a 0–100 score with BRAG evidence-linked findings, category grades, and prioritized fixes.

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What is CITE LEDGER

CITE LEDGER is the verification layer that checks whether AI systems can extract, attribute, and cite your content. A page can rank first in traditional search and still be invisible to answer engines if structural signals are missing.

AiVIS.biz measures extractability, trust signal alignment, and citation readiness across seven weighted dimensions: Schema & Structured Data (20%), Content Depth (18%), Technical Trust (15%), Meta Tags & Open Graph (15%), AI Readability (12%), Heading Structure (10%), and Security & Trust (10%). Hard-blocker caps prevent inflated scores when critical signals are missing.

What is BRAG

BRAG stands for Based-Retrieval-Auditable-Grading. Every finding is tied to verifiable page evidence using stable evidence identifiers. If something cannot be proven from the live page, it is not included in the score.

Who should use AiVIS.biz

AiVIS.biz is built for founders, marketers, developers, and agencies who need to understand why their content is not being cited by AI answer engines. If AI models are ignoring, misquoting, or attributing your content to competitors, the CITE LEDGER shows you exactly why.