Does AI know that you exist?
Ever wonder if AI can actually see you? Better yet, recommend you? Beyond Visibility is built to answer exactly that with a score, not a guess. Paste in your content, or point it at your website, and either way you get a score from 0 to 100, plus a clear list of what to fix and why. No guesswork: every tip comes from real research into how AI picks who to mention.
Products
Web Grader
Paste a live URL instead. Get a Technical Score (schema markup, AI crawler access, metadata, freshness, extractability) alongside the same Content Score, so you can see exactly what's blocking a page from being retrieved and cited.
Content Grader
Paste an article or upload a doc (PDF, Word, Markdown, plain text). Get a 0–100 score across seven weighted categories (AI Answerability, Structure & Chunking, Citations & Evidence, and more), plus quoted, prioritized fixes.
How it grades
Seven weighted categories
AI Answerability, Structure & Chunking, Citations & Evidence, and four more, each scored 0–100 and rolled into one overall grade, weighted by measured impact on citation rate.
Every deduction is quoted
Recommendations cite the exact passage that caused them, with a concrete rewrite and an estimated point impact, so you never get vague advice you have to translate yourself.
Built on retrieval research
Category weights and checks are grounded in published GEO research: quotations, statistics, answer-first structure, and clean chunking measurably lift citation rates.
Frequently asked
Is this the same as SEO?
No, but it's not a replacement either. Think of AEO as SEO's newer sibling. Classic ranking signals like crawlability, authority, and freshness still matter; retrieval just adds a passage-level layer on top, and there's no page-one click-through funnel to fall back on if that layer fails.
Do I need both the Web Grader and the Content Grader?
If you control the page, yes, eventually. Technical and Content scores catch different failure modes. A page can read beautifully and still be invisible because of one robots.txt rule. If you're evaluating a draft before it's published anywhere, the Content Grader alone is the right tool.
Which AI systems does this actually target?
The check set is grounded in how retrieval-augmented answer engines behave generally. ChatGPT, Perplexity, Claude, and AI Overviews all share the same fetch-chunk-retrieve-synthesize shape, even though none of their exact ranking algorithms are public.
How often do the rubric weights change?
Rarely, and only on evidence. Every category weight is pulled straight from the versioned rubric config the grader runs against (see the About page for the current breakdown), so a score you get today stays comparable until that version number moves.
Can a perfect Content score still not get cited?
Yes. Citation also depends on factors outside a single page: how many other pages answer the same question, how established the domain is, off-page mentions the grader can't read from text alone. The score measures your odds, not a promise.
Where do the numbers in the research callouts come from?
Primarily the Princeton GEO paper (10,000 queries across 25 domains), plus supporting industry research on content chunking, freshness, and answer-first structure. Those sources also inform the weights behind every score this tool produces.