Standalone tool

What do ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews say about you?

Drop your brand and the queries your buyers actually type. We ask each connected engine through its API with live web search, 1 sample per query, and show, per engine, whether you are named, your answer position, the verbatim answer, the model version, and the sources it cited. It is a measurement of that sample, not a ranking or a guarantee, and the consumer apps can answer differently. 3 queries free on Perplexity and ChatGPT. Paid plans check up to 25 across six AI answer engines and track them every week with 2 samples per engine.

0 / 25 queries (free snapshot, Perplexity and ChatGPT)

We poll each connected engine the way a buyer would ask, and show the verbatim answer.

  • Free snapshot: Perplexity and ChatGPT
  • Mentioned in k of N API samples, with the verbatim answer
  • We never fake a result for an engine we cannot poll

How the check works

Step 1

You name the queries

Enter your brand plus the 5 to 25 queries your buyers actually type. The richer the query set, the more reliable the per-engine read.

Step 2

We poll the connected engines

We ask each connected engine through its API with live web search: 1 sample per query on a check, 2 samples per engine on each weekly tracked refresh. LLM answers vary run to run, so a small sample is a snapshot, not a verdict. Google AI Overviews is read from the Google results page, and a run with no AI Overview is reported as not measured. Engines we cannot poll show as not connected, never a faked result.

Step 3

You get an honest read

Per-engine cards: how often you were named across the samples, your answer position, the sources the engine trusted, and the exact answer it gave, labeled with provider, model, search mode, locale, and time. With one sample the confidence range is wide, and we show it as wide.