AI Visibility Intelligence Platform
AiVIS is an AI visibility intelligence platform that audits how answer engines read, trust and cite a website.
It interprets your site's structure, trust signals and citation readiness based on real page evidence, not inferred summaries.
Get a 0-100 visibility score with evidence-backed findings and prioritized fixes.
What is AI visibility
AI visibility is the degree to which a website can be understood, trusted and reused by systems that generate answers instead of returning links.
It depends on content depth, heading clarity, schema coverage, metadata quality and machine readable formatting.
A page can rank first in traditional search and still be invisible to answer engines if these signals are missing.
Ranking alone does not earn citation. AiVIS measures the extractability, trust signal alignment and citation readiness of your content by analyzing what answer engines actually need to formulate a reliable answer.
Learn more about the audit methodology behind the scoring.
Evidence-backed visibility intelligence
Full page interpretation
AiVIS reads your page the way an answer engine does and shows where meaning breaks or becomes unclear.
Evidence IDs linked findings
Every issue is tied to a real part of your page so you can see what caused it and how to fix it.
Clear consistent scoring logic
You get a visibility score based on structure, content and trust signals that affect citation readiness. No AI guessing, hallucinations or opinions. Every finding must be validated with BRAG evidence IDs.
Actionable fixes
Each result includes direct changes that improve how your site is read and reused by AI systems.
How AI systems evaluate websites
Structure comes first
Clean headings and logical sections help models understand what each part of the page means without guessing.
Clarity beats volume
A long page does not help if the meaning is unclear. AI prefers content that is easy to break into usable parts.
Trust is earned through signals
Consistent naming, schema and supporting details increase confidence in what the page is saying. Use the free structured data impact validator to check your schema coverage.
Alignment with real user questions
Content must match how users actually ask questions or it will not be retrieved.
What AiVIS actually audits
Content depth
Whether your page has enough substance to support extraction, summarization and reuse.
Heading hierarchy
Whether your structure helps or blocks understanding across sections.
Entity clarity and authority
Whether your site clearly defines what it is and how it should be trusted and understood by machines.
Structured data
Whether your schema supports your content or conflicts with it.
Technical foundation
Whether performance, crawlability, robots, SPA and accessibility are blocking interpretation.
Citation readiness
Whether your content can be safely used inside AI generated answers.
Who benefits from AI visibility audits
AI visibility audits help anyone whose content needs to appear inside generated answers.
If your site depends on being found, trusted and reused by AI systems, this audit shows you exactly where visibility breaks and how to fix it.
Founders and product teams
Understand whether your product pages, documentation and landing pages are readable by AI systems that potential customers use to evaluate solutions before they ever visit your site.
Marketing and content teams
See which content assets are eligible for citation, which are being ignored, and what structural changes unlock retrieval across ChatGPT, Perplexity, Claude and Google Gemini.
Developers and technical leads
Audit schema markup, heading hierarchy, canonical tags and structured data against the signals AI models use to build trust, resolve entities and extract usable content.
Power users and consultants
Offer clients measurable proof of AI visibility health with a structured report that connects every finding to actual site evidence through BRAG evidence integrity identifiers.
Based Retrieval and Auditable Grading
AiVIS uses BRAG which stands for Based Retrieval and Auditable Grading. Every finding is tied to verifiable page evidence using stable evidence identifiers.
Each element of your page is assigned a BRAG evidence ID so results can be traced, verified and rechecked across scan cycles.
If something cannot be proven it is not included. If something is missing it is shown as missing. Learn more about BRAG, or customize it for your needs.
From audit to citation
An audit is the starting point. AiVIS also supports how AI citation testing works to verify whether AI models reference your brand in live answers.
You can run competitor visibility tracking to benchmark your visibility against rival sites.
Review the audit methodology to understand how each category is scored or use the structured data impact validator to check your schema coverage.
Frequently asked questions about AI search visibility
What is AiVIS
AiVIS is an AI visibility intelligence platform that audits how answer engines read, trust and cite a website. It crawls your page, extracts structural signals and maps them to a 0-100 visibility score across six weighted categories. Every finding is tied to real page evidence through BRAG evidence identifiers so results can be verified and traced, not assumed.
What is AI visibility
AI visibility is the degree to which a website can be understood, trusted and reused by systems that generate answers instead of returning links. It depends on content depth, heading clarity, schema coverage, metadata quality and machine-readable formatting. A page can rank first in traditional search and still be invisible to answer engines if these signals are missing.
What causes low AI visibility scores
Common causes include thin content with fewer than 800 words, missing or conflicting structured data, unclear heading hierarchy, absent metadata, weak entity signals and poor technical foundations like blocked crawlers or slow load times. AiVIS identifies each gap with evidence so you know exactly what to fix and in what order of impact.
How does AiVIS find visibility issues
AiVIS crawls the target URL with a real browser, extracts structural signals including headings, schema, meta tags, body content and links, then runs them through a multi-model AI pipeline that scores each category. On higher tiers a second model critiques findings and a third validates the result. Every issue references specific page evidence through BRAG identifiers.
What is citation readiness
Citation readiness measures how safe and reliable a page is for reuse inside AI-generated answers. It requires clear entity definitions, consistent schema support, sufficient content depth and structural formatting that allows AI systems to extract usable information without risking attribution errors or factual misrepresentation.
What is BRAG in AiVIS
BRAG stands for Based Retrieval and Auditable Grading. It is the evidence framework that ties every audit finding to a real element on your page. Each heading, schema block, meta tag and content section receives a BRAG evidence identifier that can be traced, verified and rechecked across scan cycles so no finding is left unsupported.
Why does structure matter for AI systems
Structure allows AI models to break content into context-appropriate sections without losing meaning. Clean headings, logical section flow, consistent naming and proper schema help answer engines determine what each part of a page means, how it relates to the broader topic and whether it can be safely extracted and cited as a source.
Who should use AiVIS
AiVIS is built for solofounders, marketers, developers and power users who need to understand why their content is not being used by AI answer engines. If your site depends on being found, trusted and reused by ChatGPT, Perplexity, Claude or Google AI, the audit shows exactly where visibility breaks and what changes will fix it.
