Guide · AI visibility
LLM visibility tools
"LLM visibility" is the same measurement described from the model's side rather than the search engine's. It matters because a brand's presence is rarely even across models: being named by ChatGPT says very little about whether Gemini or Claude will name you.
Which models to cover
ChatGPT and Google's Gemini carry most of the consumer volume. Perplexity matters disproportionately for research-heavy buying, Claude for technical audiences, and Copilot for anyone inside a Microsoft-heavy company. A single-model tool is measuring a fraction of the picture.
Why the split matters
Models draw on different sources. One leans on live search results, another on its training data, another on a small set of trusted publishers. When a brand appears in one and not another, that gap names the fix: the missing model is reading sources you are absent from.
Grounded vs ungrounded answers
Answers built from live retrieval can be changed in weeks by publishing the right page. Answers built from training data move far more slowly. A tool that does not distinguish between the two will tell you to fix something that no amount of publishing can shift this quarter.
See where your brand stands
Free, no account: the questions you lose and the competitor named instead.
Common questions
- Is LLM visibility different from AI search visibility?
- In practice the terms are used interchangeably. AI search visibility usually emphasises engines with live retrieval; LLM visibility includes answers built from training data alone.
- Can visibility be bought?
- No. There is no paid placement inside model answers. Presence comes from the sources models read.
Comparing products? See the ranked list of AI visibility tools, including our own measurement of which tools AI engines name.