What Peec AI (and tools like it) actually do
The category runs a defined set of prompts - real questions a buyer might ask - against multiple engines (ChatGPT, Perplexity, Gemini, and others, coverage varies by vendor) on a repeated schedule. It logs which brands appear in the answers, how prominently, whether they're cited with a source link, and tracks share-of-voice and sentiment over time against named competitors.
The honest limitation: the prompt set is the ceiling
Visibility and share-of-voice, as these tools report them, are measured only over the tracked prompt set - not over every question anyone could ask. Adding, removing, or reweighting prompts changes what gets measured, not what the engines actually say elsewhere. A rising visibility score against a static, well-chosen prompt set is a real signal; the same score treated as "how visible we are in AI, period" is a misreading.
Where it fits in a real measurement stack
An answer-tracking tool measures one surface: what engines say. It does not measure what engines actually fetch from your site (that needs crawler-log analysis) or whether AI-referred visitors do anything once they arrive (that needs traffic and outcome measurement). Treat the three as separate instruments that need to be read together, not one tool standing in for all of it.
Why we use tools in this category
As one instrument inside the AI visibility audit, not a substitute for it. Raw output from any answer-tracking tool still needs competitor-set curation, interpretation against your actual business questions, and translation into a prioritized fix plan - the part a dashboard alone does not do.