AI visibility tools that publish their prices

What do AI engines say AI visibility tools cost?

We track two pricing questions in our own workspace. Asked "AI search visibility starting price" on 4 October, ChatGPT answered with the price list at the top of this page, from $9 a month for WhiteRank to $1,499 one-time for a done-for-you assessment. It read attensira.com/pricing among its sources and still did not name Attensira; the chart above shows that is the pattern, not a one-off.

Asked "affordable AI visibility tool for startups" on 3 October 2026, ChatGPT answered with a price table: Otterly.ai at $29 a month, Rankscale around $20, AthenaHQ free, Cituna at $39, Peec AI around $95, and Profound at $99 a month billed annually. Attensira was not named.

Most of those match the vendors' own pages or close to it. One does not. When we read Profound's pricing page the next day, it listed a free trial and a custom Enterprise plan, and no $99 plan. The answer drew its prices from comparison pages, and a comparison page can be out of date or wrong. That is the practical case for published pricing: when a vendor publishes, a buyer can check the answer; when it does not, the engines guess, and the guess becomes what buyers believe.

Why does published pricing matter more in AI search?

Because buyers increasingly ask an assistant before they ever reach your site, and "how much does X cost?" is one of the first questions they ask. If your page states the price clearly, the engine can quote it. If it does not, the engine quotes whatever it finds elsewhere, a review site, a reseller, an old blog post, or says the price is unknown and moves on to a competitor that published.

That applies to Attensira as much as anyone. Our plans and the price of the work are on the pricing page and in public documentation, written so that an engine can quote them correctly.

How does Attensira price the work?

Credits first. A plan pays for monitoring and includes a monthly allowance of credits for agent work. One credit is one cent. Agents spend credits as they work, research, drafting an article, preparing a fix, writing a pitch, and reading the numbers you already have never spends any.

Beside the plan you set a monthly budget. It is a ceiling, not a prepayment: work is charged as it runs, work that never ran is never charged, and once the month's spend reaches the budget, new work pauses until you raise it or the month turns. The pricing page shows the budget as the work it buys, so you see "this many articles, this many fixes, this many pitches" rather than a number of credits. If the crew delivers less than the budget committed for the month, the difference comes back as credit.

Which published price suits which team?

Testing on a small budget. Otterly.AI Lite or LLMrefs.

Wanting an SEO suite with AI inside. Moz, where every extra is priced, or SE Ranking and Semrush, which publish prices in their own currencies.

Wanting to know the answer volume. Promptwatch or AthenaHQ.

Wanting articles in the price. Writesonic.

Wanting the work done, with the cost known in advance. Attensira.

How should a pricing page be written so engines quote it correctly?

If you sell software, the lesson of this page applies to your own pricing page. Engines quote what they can read. A price shown only in a script-rendered widget, in an image, or behind a toggle that defaults to annual billing is easy to misquote. A price in plain text, with the billing period beside it, is easy to quote correctly.

Four habits help. State each plan's price and what it includes in a sentence, not only in a table cell. Say whether the price is monthly or billed annually, every time. State the trial terms, including whether a card is needed and what happens at the end. And keep one canonical pricing page rather than prices scattered across feature pages and blog posts, because engines will find the old ones too.

Attensira's own pricing page and its public plans documentation are written that way, which is also why the answers our engines give about our prices can be checked against a page that says the same thing.

Which numbers should any AI visibility price page show?

Use this as a checklist when you read the pages above, or any other.

• The price, per month, with the billing period. Monthly and annual side by side.
• How many questions you can track. Prompts, slots or queries, and whether the number is a stock you

hold or a flow that resets.

• Which engines are included, and which cost extra.
• How many answers that buys. Responses per month, or the sampling depth per reading, so you can

tell a rate built on hundreds of answers from one built on a handful.

• Seats. Included, extra, or unlimited.
• Trial terms. Length, card, and what happens at the end.
• What happens after the finding. Whether the price includes any work, and if so how much.

No page we read shows all seven. Otterly.AI, Moz and Promptwatch come closest on the tracking side; Attensira's plans documentation covers the tracking numbers and the price of the work, with the budget shown as what it buys.

When is Attensira the wrong pick?

When you only want tracking at the lowest price, Otterly.AI or LLMrefs cost less. When you need the most engines on one published plan, AthenaHQ reads more. Attensira's published price includes the work, and is for the team that wants agency-level AI-search work at a published software price, with you approving each piece.

Before you buy any of them, open the vendor's page yourself; the links are in the sources below.