See how ChatGPT, Gemini and Perplexity describe your brand right now. One name in, a 0–100 score per engine out, with the sources and competitors behind it.
Live query against ChatGPT, Gemini and Perplexity. Takes 20–60 seconds. Three free checks an hour. Score and verdict are free; the per-engine breakdown opens with one email.
The check above is one run on one prompt set. Leave your email and we will look at how your category is being answered and send back where the citations are going instead.
When a buyer asks ChatGPT, Gemini or Perplexity for a recommendation, the engine assembles an answer from what it has read about the category and the brands in it. AI visibility is whether your brand is in that answer, how it is characterised, and whether it survives the follow-up questions that narrow the shortlist. This checker asks each engine to research your brand and reports what came back: an awareness score, a sentiment read, the sources the engine leaned on and the competitors it put next to you.
The blended score is deliberately simple. It is the average of the awareness ratings from the engines that answered, on a 0–100 scale, so that a brand that is well known to ChatGPT but unknown to Perplexity lands in the middle rather than being flattered by its best engine. The per-engine cards underneath are where the diagnosis lives.
ChatGPT is the largest consumer answer engine and the one most buyer research starts in; its score is the closest thing to a headline. Gemini powers Google AI Mode and AI Overviews, so a low Gemini score usually means your traditional search presence is not translating into AI answers either. Perplexity is citation-first and rewards pages that answer a question in the first paragraph; its sources list is the most actionable of the three.
Two signals matter more than the number. The competitors named alongside you are the shortlist the engine already keeps for your category, and their scores tell you how far ahead they are. The prompts the engine associates with you are the questions it thinks you answer; if they are generic or wrong, the engine has not understood what you sell, and that is an entity problem before it is a content problem.
A score under 20 almost always means the engines have little third-party text about the brand. The fix is not more marketing copy on your own site; it is unambiguous entity signals (one canonical name, an About page, Organization and Product schema) and mentions on the review, comparison and community sources the engines already cite for your category. Those sources are listed under each card.
A score between 20 and 50 means the engines know you but do not recommend you. Here the work is answer-shaped content: a page per buyer prompt, with the answer in the first two sentences, a comparison table where the prompt is comparative, and FAQ markup that matches the questions on the page. Above 50, the remaining gap is usually the follow-up turn, where a buyer adds a constraint (price, integration, compliance) and a competitor with a specific page on that constraint takes the slot. Tracking finds those turns.
This page is a checker: one brand, one run, three engines, now. It answers "where do I stand today". It cannot tell you whether you are improving, which specific prompts you are losing, or what changed last week, because every run is a fresh, non-deterministic answer.
To track your AI visibility over time, Sprites runs a fixed set of buyer prompts on a schedule, records mentions, position, sentiment and citations per engine, and turns the losses into page-level work. It does that inside the same agent that runs your SEO and paid media, so a lost citation becomes a rewritten page rather than a dashboard alert. The checker is the free front door; the tracking is the product, and the improve AI visibility hub explains what the category means and why it matters.