NES
AI Visibility Score · Free · ~1 minute

What does AI say about your brand when you’re not in the room?

A growing share of buying decisions starts with an AI answer, not a search page. This free check asks a leading AI model about your brand with no access to your site, then scores what it says, 0 to 100, against what your website actually promises.

Run the free AI visibility check

No login. Score on screen in about a minute.

Common questions

AI visibility score FAQ

What is an AI visibility score?

An AI visibility score measures how well AI assistants like ChatGPT, Claude, and Perplexity know and describe your brand. This checker asks a leading AI model what it knows about your brand with no access to your website, then scores the answer 0-100 across five components: recognition, accuracy, specificity, sentiment, and consistency with what your site actually says.

Why does AI visibility matter for my brand?

A growing share of product research now starts with an AI answer instead of a search results page. If AI models do not know your brand, or describe it inaccurately, you lose consideration before a prospect ever reaches your website. AI visibility is becoming what page-one rankings used to be.

Is the AI visibility check free?

Yes. The check is free and takes about a minute. It is a standalone free tool powered by the Net Entropy Score framework; deeper brand-consistency reads are separate paid tiers.

How do I improve my AI visibility score?

AI models learn brands from consistent public signal: a website that states clearly what you do and for whom, third-party mentions, reviews, and press that all tell the same story. The biggest lever is consistency, because models synthesize across sources; a brand that describes itself differently everywhere gets a vague or wrong AI description.

Which AI model does the checker use?

The current check reads one leading frontier model (Anthropic's Claude). Model knowledge overlaps heavily across major AI assistants because they train on similar public data, so a low score on one model usually indicates low visibility across all of them.