Why track more than one AI engine?
Because each engine can give a different answer to the same question. A brand can do well in one and be missing from another. If you only watch one, you only see part of the picture.
The term AI engine tracking refers to running the same prompts through Perplexity, Gemini and Claude and comparing how each one answers.
The engines also work in different ways. Some look things up on the web before they answer. Others answer from what they already know. Knowing which is which helps you read the results properly and decide what to do about them.
It also explains a common puzzle. People often ask why their brand is named in one engine and missing in another for the same question. Sometimes it is because one engine found a list that includes you and the other didn't. Sometimes it is because one engine answered from memory. The side-by-side view makes that much easier to spot.
How do Perplexity, Gemini and Claude differ?
Perplexity and Gemini search the web and cite pages. Claude can be asked both ways, from memory or with web search. The table sets out what that means in practice.
| Engine | How it answers here | Sources shown | Credits per query |
|---|---|---|---|
| Perplexity (Sonar) | Searches the live web, then writes an answer | Yes, cited pages | 20 |
| Google Gemini | Searches Google, then writes an answer | Yes, cited pages | 24 |
| Anthropic Claude | From what the model already knows, no web search | No | 32 |
| Claude with search | Searches the web, then writes an answer | Yes, cited pages | 60 |
Perplexity
Perplexity looks up pages on the web and writes its answer from them. It then lists the pages it used. That makes it a close cousin of ChatGPT tracking, since both show you which sources shaped the answer. The two often choose different sources, though, so it helps to track both.
Gemini
Gemini is asked through its API with Google Search switched on. So it searches Google, writes its answer and names the pages it used, much as Perplexity does.
You can also add the Gemini app as its own engine. That collects the answer as the Gemini app shows it, with its sources, so you can see how close the app is to the API. Each app answer costs 12 credits on Professional plans and above.
Claude
Claude is asked through its API with web search turned off. So it answers from what the model learned in training. That shows how the model itself sees your brand, with nothing looked up on the day.
This is useful in its own way. If the model describes you well, that suggests your business is widely and clearly described. If it gets you wrong or leaves you out, that points to a gap in how you are described across the web. Changes here tend to show up when the model is updated, not overnight.
Claude with search
Claude with search is a separate engine you can switch on next to plain Claude. It lets Claude search the web before it answers, the way the Claude app does, and it names the pages it used. That shows how Claude talks about you today, including recent pages and newer brands the model has not learned about yet. It costs 60 credits an answer, because the pages it reads add to the work, and it is on Professional plans and above.
How does tracking work?
It runs the same prompts through each engine you choose and reads every answer the same way.
- Use your prompt set. The same buyer questions run across every engine, so results are easy to compare.
- Pick the engines. Turn on Perplexity, Gemini and Claude alongside ChatGPT and Google AI Overviews.
- Run on a schedule. Each run adds to the history, which smooths out the natural variation between answers.
- Read each answer. Every answer is checked for mention, position, sentiment, competitors named and whether you were recommended.
- Keep the sources. For Perplexity and Gemini, the cited pages are stored with each answer.
Most answers are collected through the APIs, so every run is asked the same way. The Gemini app option collects the answer as the app shows it, through a data provider. A person's own app can still differ a little because of their history, location and model version.
What do you see on screen?
You see each engine side by side, so gaps stand out. A chart shows share of voice and prominence per engine over time. You can open any answer to read it in full.
For Perplexity and Gemini, the cited pages feed into AI citation tracking. For Claude there are no cited pages, so the focus is on what it says and how often it names you.
What if Gemini or Claude get your details wrong?
That is a common problem, and it is one that AI answer accuracy checks are built for. Each answer is broken into claims and checked against your approved fact sheet. Gemini names the pages it used, so the source is often clear. Claude names no source, so a source finder searches for pages that state the wrong detail. It checks the pages other engines cited for the same question, your own website and Google, and shows the matching text.
Our guide on how AI engines choose sources explains why engines with and without web search behave so differently.
Who uses it?
Brands that sell nationally tend to track all the engines, because buyers use different ones. B2B and software firms often care most about how the models describe them, since buyers ask for comparisons. Agencies use the side-by-side view to show clients where they are strong and where they are missing. Each query has a published credit price, shown on the pricing page.
Where it fits
These engines sit inside AI visibility tracking with ChatGPT and Google AI Overviews. ChatGPT visibility tracking covers the other search-enabled engine. AI answer accuracy checks catch wrong details, and the entity audit checks how clearly your site describes your business.