Peec Charges Per Prompt and Model
Peec vs. Profound
Peecs pricing works because AI visibility is not a database business, it is a metered compute business. Every tracked question has to be rerun inside ChatGPT, Gemini, Claude, and Perplexity to see current rankings, citations, and brand sentiment, so cost scales with each prompt and each model. That is why Peec charges on prompts and models tracked, while making seats free so whole marketing teams and agencies can review results without adding marginal delivery cost.
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This is the opposite of classic SEO economics. Semrush built on cheap, repeatable scraping of Google results, then grew to $444M of 2025 revenue before Adobe agreed to buy it for about $1.9B. Peec has a much higher cost of goods, but also a cleaner usage based pricing unit.
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The workflow is very concrete. A marketer loads the questions buyers ask, then Peec runs those prompts every day across major chatbots and shows where the brand appears, what sources the models cite, and how the answer frames the company. More prompts, more models, and more client accounts all create direct incremental cost.
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Free seats make agencies especially attractive customers. About half of Peecs base comes from agencies, which can start with a couple of clients and expand to 25 or more. That expansion lifts tracked prompt volume faster than headcount, which fits a product whose real bottleneck is model query spend, not user access.
The category is likely to keep moving toward hybrid models where monitoring and execution are bundled together, but the billing logic will still center on usage. As AI search becomes a larger discovery and transaction surface, the winners are likely to price like infrastructure on the back end, even when they sell like marketing software on the front end.