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.

How to Audit AI Answer Readiness | AiVIS.biz

An AI answer readiness audit measures whether your content is structurally prepared for extraction by ChatGPT, Perplexity, Gemini, Claude, and other answer engines. Here is what the audit evaluates and why.

What an AI readiness audit measures

Unlike a traditional SEO audit focused on rankings and backlinks, an AI readiness audit evaluates extraction fidelity: can AI models access your page, parse the content, identify the publisher, and reproduce claims accurately?

AiVIS.biz audits six dimensions: content depth (20%), schema coverage (20%), AI readability (20%), technical SEO (15%), metadata quality (13%), and heading structure (12%). Each dimension targets a specific extraction failure mode.

How the BRAG evidence protocol works

Every finding in an AiVIS.biz audit includes a BRAG Evidence ID (Based Retrieval and Auditable Grading). This ID links the finding to the source signal on your page, the extraction rule that triggered it, and the scoring dimension it affects.

The protocol eliminates speculative recommendations. If AiVIS.biz cannot observe a signal on the page, it does not generate a finding for it. Every recommendation maps to verified crawl evidence.

Running your first audit

Enter any public URL into AiVIS.biz. The system crawls the page via headless browser, extracts all structural signals, scores six dimensions, and delivers a composite score from 0 to 100 with prioritized fix recommendations.

Observer tier (free) provides the score and top blockers. Starter and above provide all recommendations with implementation code and evidence detail.

Frequently Asked Questions

How often should I audit my pages?: After any significant content or structural change, and at minimum monthly. AI model behavior evolves, so periodic re-audits catch both site regressions and model-side changes.
Can I audit competitor pages?: Yes. On Alignment tier and above, you can add competitor domains and compare extraction readiness across shared topics.