Free AI visibility checker: does AI name your brand?
Type your brand and category. We ask live AI engines 3 questions a buyer would ask, without ever mentioning your name, and show you which engines brought you up on their own.
By Vladimir Boldyrev · LLMBrandScan · Published October 2, 2026 · Reviewed October 2, 2026
Live engine status (2026-10-18): ChatGPT (API with web search), Gemini (grounded), Claude (API with web search) and Google AI answers (AI Overviews) are answering. Perplexity Sonar is temporarily unavailable at the provider — scans run on the engines that answer, and an engine that does not answer is not charged. This note updates by itself when an engine comes back.
Engines asked right now: ChatGPT (API with web search) and Gemini (grounded).
The free AI Visibility Checker asks live AI engines 3 buyer-style questions about your category and reports, engine by engine, whether your brand was named. None of the questions contains your brand name, so the result shows unaided recall: whether the model brings you up by itself when a buyer asks for options, not whether it can repeat a name it was handed. The check is deliberately small. It takes one brand, up to two competitors, one run per person per day, and only engines that are answering right now. Because AI answers vary from one run to the next, one pass is a signal, not a measurement. The $19 Quick check asks 10 questions on 3 engines and samples each one several times, 90 answers in total, then reports a range instead of a single number.
The 3 questions we ask.
Each question is built from your category alone. Three different phrasings of the same buying need beat one question asked three times.
- What are the best {your category}?
- Which {your category} would you recommend for a small business, and why?
- I'm choosing between {your category} — what are the top options right now and how do they compare?
How to read the result.
Named or not, per engine
An engine counts as naming you when your brand appears as a whole word in at least one of its answers. An engine that failed to answer is shown as unavailable, never as a miss.
Share of voice against two competitors
Your named answers divided by the answers naming you or either competitor. It is a first-look ratio from a handful of answers, not a market-share figure. The method is in the AI share of voice formula.
What a single pass cannot tell you
AI answers change from run to run, so one miss does not prove you are invisible. If the free check names you nowhere, that is the cue to run the paid sampled version — see how AI visibility is measured.
Free check or Quick check.
| Free check | Quick check | |
|---|---|---|
| Price | Free, once a day | $19, one time |
| Questions | 3, fixed | 10, edited by you |
| Samples per question | 1 | Several, reported as a range |
| Competitors | Up to 2 | As many as you enter |
| Result | Mentioned or not, per engine | Full report with sources and lost slots |
A Quick check is 10 questions × 3 engines × 3 samples = 90 answers. See what it looks like in the sample report.
Questions about the free check.
Is the AI visibility check really free?
Yes. One check per person per day costs nothing: no card, no account, no credits. We ask for an email address only to enforce the one-a-day limit, and we do not send mail to it. LLMBrandScan itself is a paid product, so the free check is deliberately limited to a single small run.
Which AI engines does the free checker use?
Only engines that are answering at the moment you run it, taken from the ones the Quick check uses. Right now: ChatGPT (API with web search) and Gemini (grounded). If an engine is down it is skipped, and the result says so instead of counting a failure as "not mentioned".
How is the share of voice calculated?
It is your brand's answers divided by the answers that name your brand or either competitor you entered. An answer that names none of them is not counted. If nobody you track is named at all, the result says so rather than showing 0%.
Why can the result differ from what I see in ChatGPT?
AI answers are non-deterministic and depend on location, account history and model version. The free check asks each question once per engine, so treat it as a first look. The paid Quick check repeats every question several times to show a range.
Keep reading.
- AI Visibility AuditWhat a one-time audit measures, what lands in the report, and what it costs — before you spend anything.
- LLM SEO ToolA measuring tool for LLM SEO: where AI answers name you, who they name instead, and which sources they lean on.
- Best AI Visibility Tools ComparedOtterly, Peec AI, Profound, Ahrefs Brand Radar and Semrush next to a one-off scan — prices checked on the vendors' own pages.
- LLMBrandScan vs. ProfoundProfound's published pricing and scale as of mid-2026, next to what a one-time scan costs and covers. Every number sourced and dated.
- LLMBrandScan vs. Peec AIWhat Peec AI costs and covers as of mid-2026, and the honest decision rule for continuous monitoring versus a single dated audit.
- What Generative Engine Optimization (GEO) Actually MeansThe definition, how it differs from SEO, and why 'optimizing for AI answers' is a different job than optimizing for a ranked list.
- Answer Engine Optimization (AEO): Myths vs. FactsAEO, GEO, and LLM SEO get used interchangeably online. Here's what's actually true about each — and where the myths come from.
- How to Create an llms.txt File (Step by Step)A working llms.txt template, what belongs in it, and an honest read on what it does and doesn't do for AI visibility.
- AEO vs. GEO: A Head-to-Head ComparisonThe two acronyms compared axis by axis — origin, scope, mechanics, what each one measures — and a decision rule for which one your work actually is.
- GEO vs. AEO vs. LLM SEO: What's the Actual Difference?Three overlapping terms for three overlapping-but-distinct jobs. A disambiguation guide so you stop guessing which one you need.
- What Is AI Visibility, and How Is It Actually Measured?The metrics the category has converged on — Visibility Score, Share of Voice, first-mention — explained from first principles.
- How to Improve Your Odds of Being Recommended by ChatGPTSeven concrete, testable levers — and three things that don't work no matter how confidently they're sold to you.
- How Perplexity Chooses Sources to CiteThe mechanics of Perplexity's citation model, what makes a page citable, and how to track whether you're being cited at all.
- Optimizing for Google AI OverviewsWhat triggers an AI Overview, how it differs from classic SGE and organic ranking, and a practical checklist to work through.
- AI Brand Monitoring: Why a One-Time Check Isn't EnoughAI answers drift month to month. What ongoing monitoring actually requires, and the DIY-vs-tool tradeoffs honestly laid out.
- AI Share of Voice: The Formula and a Worked ExampleThe exact formula, a worked numeric example with real arithmetic, and how it maps onto the classic marketing metric it's borrowed from.