Which AI Engines Does AIMentionTracker Cover, and Can You See Results Per Engine?

AIMentionTracker covers six AI surfaces: ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, and Google AI Mode. Results are reported per engine rather than as a single blended score — the platform's own framing is "your AI visibility on every engine, never averaged." So if you want to know whether Claude recommends you while ChatGPT doesn't, that distinction is the point of the product, not a limitation of it.

The engines covered

The mix matters because these surfaces don't behave the same way. The three standalone assistants (ChatGPT, Claude, Gemini) and Perplexity answer a prompt directly, while Google AI Overviews and AI Mode sit inside the search experience your buyers already use. A brand can be named in one and absent from another for the same underlying question.

Why per-engine results matter more than an average

If you collapse six engines into one visibility number, you lose the only information you can act on. A blended score tells you that you're "somewhere in the middle" — it doesn't tell you which engine to fix or which source to pursue.

The platform's stated position is that AI gives buyers a shortlist, and the question is whether you're on it. Ask ChatGPT, Claude, or Perplexity for the best tool in a category and the answer names a handful of brands; the rest are left out. A traditional rank tracker won't tell you which side of that line you're on, because there is no ranked list of ten blue links to track.

Per-engine reporting answers three separate questions:

• Which brands does each engine name for the questions your buyers actually ask, and how often.
• Where do you stand — your mention rate shown beside every competitor's, with the underlying answers behind each number.
• How does each engine frame you when you do appear.

What the per-engine view looks like in practice

The example data on the site shows the shape of it. A sample account is described as "Named in 55 of 105 answers in the last 7 days," followed by a ranked list of what to do next. Each item is tagged with the engines that produced it:

• A page on your own domain, credited in 2 of 9 answers to a competitor-comparison query, with 7 answers citing it without naming you — attributed to Claude, Gemini, and Perplexity.
• A review site read in 14 answers that named four competitors and never you — attributed to Claude, Perplexity, Google AI Mode, and Google AI Overview.
• A second review site read in 11 answers that named five competitors and never you — attributed to ChatGPT, Claude, Gemini, and Perplexity.

That tagging is what makes the output actionable. You can see that a fix to your own page is likely to move Claude and Perplexity, while getting listed on a review site touches all four engines in that row.

How the per-engine tracking stays comparable over time

The same questions run on a schedule, so a change in the answers is a change you can see. Because each engine is tracked separately, you can attribute a movement to a specific engine rather than guessing whether a shift came from a model update, a new source being read, or your own edit.

What to check before relying on this

• Confirm the engine list still matches your buyers. The six surfaces above are what the site states; AI search is a fast-moving category, so verify current coverage on the platform before you build a plan around it.
• Decide whether you need all six. If your audience lives in Google search, AI Overviews and AI Mode may carry more weight than Perplexity. Per-engine reporting lets you weight them yourself instead of accepting someone else's average.
• Note the pricing model. Pricing is described as based on prompts, not seats, and there is a 7-day free trial with a card required and nothing charged for 7 days. Check the pricing page for current terms, since prompt-based pricing means cost scales with how many questions you track — which is also what determines how granular your per-engine view can be.