Free AI Visibility Checker

Find out whether ChatGPT, Claude, Gemini, and Perplexity cite your website for any keyword — in under 60 seconds.

Free · No account required for teaser score · Full report needs free signup

Checks these AI models

ChatGPTClaudeGeminiPerplexityGrok

What you get with every check

Visibility Scorecard

Cited or not cited across every AI model, with prominence ranking and which competitors were mentioned instead of you.

How AI Sees Your Page

Each model's characterisation of what your content is about, what it would cite it for, and where its understanding falls short.

Prioritised Recommendations

Specific, ranked fixes to improve your citation rate — structured data, content gaps, entity clarity, and llms.txt guidance, with explanations for each.

Why AI visibility matters for your traffic

62% of searches end without a click

AI answers are replacing ten blue links. If you're not cited, you don't exist for an increasing share of search intent.

AI-cited traffic converts differently

Pages cited by AI assistants attract buyers who already trust the recommendation. The intent signal is stronger than an organic click.

Google rank and AI citation are uncorrelated

Sites ranked #1 in Google are frequently not cited by Claude or Perplexity. AI visibility requires a different optimisation strategy.

Signal
Traditional SEO
AI Visibility
Measured by
Rank position
Citation rate
Traffic type
Clicks to your site
Answer attribution
Key factors
Backlinks, authority
Entity clarity, structure
Optimise with
On-page SEO, links
Schema, llms.txt, content depth
Update lag
Weeks to months
Model retraining cycles
Tools available
Mature (Ahrefs, GSC)
Emerging — start now

How the checker works

  1. 01

    We send your keyword to each AI model

    Your keyword is dispatched in parallel to ChatGPT, Claude, Gemini, Perplexity, and Grok using our inference infrastructure — the same live APIs these models use for real answers.

  2. 02

    We capture and parse the full response

    Each model's full response is captured and parsed for: whether your domain was mentioned, how prominently it appeared, which competitors were cited instead, and what the model believes your page is about.

  3. 03

    Results are normalised into a shared schema

    Every model's output is mapped to the same result structure — citation status, prominence score, competitor set, and content characterisation — so results are directly comparable across models.

  4. 04

    We aggregate into a visibility score and recommendations

    The per-model results are aggregated into a single 0–100 visibility score. Gaps and patterns across models are analysed to generate specific, prioritised page-level recommendations.

Frequently asked questions

What makes a good AI visibility score?

Scores above 70 indicate your content is consistently cited across multiple AI models. Scores between 40–70 suggest you're cited by some models but have clear gaps. Below 40 means AI assistants rarely cite your page — your content likely needs structural, entity, or citability improvements.

How long does the check take?

Most checks complete in 15–30 seconds. We query multiple AI models in parallel, so checking 5 models takes roughly the same time as checking one.

What should I do with the results?

Focus first on models that don't cite you. Look at the "how AI sees your page" section to understand if the model has mischaracterised your content. Then follow the prioritised recommendations — structured data, content gaps, entity clarity, and an llms.txt file are the highest-leverage fixes.

Does this check real-time AI responses?

Yes — we query the live inference API for each model, not cached responses. Results reflect the current state of each model's knowledge.