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.

AI Ignores My Website Content — Diagnosis Guide | AiVIS.biz

AI does not ignore your content out of preference. It ignores it because something in the extraction chain broke. Let's find exactly where.

AI doesn't read — it extracts

Human readers can understand poorly structured content through context and patience. AI extraction pipelines cannot. They look for specific structural signals: headings, schema markup, rendered HTML, entity metadata. If the signals are missing, the extraction yields nothing usable.

This is why technically thin but structurally sound pages often outperform rich but unstructured content in AI answers.

The full chain that must not break

Step 1 — Crawler access: Your robots.txt must allow GPTBot, ClaudeBot, and PerplexityBot. Most CDN configurations block them silently.

Step 2 — Content delivery: Content must be in the HTML server response, not assembled by JavaScript in the browser.

Step 3 — Structure: Semantic headings, Organization/Article/FAQ JSON-LD, canonical URLs.

Step 4 — Attribution: datePublished, author, publisher declared. Without these, the extracted fragment has no verifiable source.

Frequently Asked Questions

Does Google indexing mean AI can use my content?: No. Google crawling and AI extraction are independent processes with different crawlers and different structural requirements. Google can index a page that AI models cannot extract.
My content ranks well in Google but never appears in AI answers — why?: SEO ranking signals (backlinks, keyword relevance) are orthogonal to AI extraction signals (schema, rendering, crawler access). You can dominate Google results and still fail AI extraction entirely.