Tools for tracking and improving how AI answer engines cite your brand, from visibility monitoring to answer engine optimization, with engine coverage and pricing compared.
Listed alphabetically, because nothing here is ranked. Compare them against the selection criteria on the right and the billing models below.
| Tool | What it does | Starts at | Getting started |
|---|---|---|---|
 AthenaHQ | AI search visibility tracking with a fully published price list | 295 USD per month for Starter, with a 17 percent annual discount | Free tier |
 Evertune | Samples each prompt 100 times, and sells ad placement inside AI answers | Not published. Pricing is quote only. | Sales contact required |
 GetCito | AI visibility monitoring with a local and regional emphasis | 599 USD per month for Growth, 999 USD for Scale, with a free self-hosted plan | Free tier |
 Goodie | Answer engine optimization sold as software and service, including AI shopping | Not published. Demo or sales contact required. | Sales contact required |
 LLMrefs | One plan, 500 prompts, every engine, unlimited seats | 79 USD per month, single tier | Free trial |
 OtterlyAI | AI search monitoring from 29 USD, with newer engines sold separately | 29 USD per month for Lite, or 25 USD billed annually | Free trial |
 Peec AI | AI visibility analytics with a published feature matrix and unpublished prices | Not published. Starter, Pro and Advanced tiers are named without prices. | Free trial |
 Profound | Enterprise AI search visibility, including how AI crawlers read your site | Not published. Pricing is quote only, via demo request. | Sales contact required |
 Rankscale | Tracks 17 or more AI engines, with page audits and prompt volume research | Not published. Demo or signup required. | Sales contact required |
 Scrunch AI | AI visibility monitoring that also serves separate page versions to AI agents | Not published on the homepage. Pricing is behind a demo or the pricing page. | Free trial |
 Surfer SEO | Content optimization scoring plus AI answer tracking, sold by document credits | 49 EUR per month for Discovery, 1 seat and 120 documents | Paid from day one |
This is the newest category on the site and the one where the gap between what is measured and what is understood is widest. Roughly two years old as a commercial category, it exists because AI answer engines started taking queries that used to produce clicks, and nobody could see what was happening inside them.
What these tools genuinely do well is measurement. They ask engines questions on your behalf, at scale and on a schedule, and record whether you appear, how you are described, and who is cited instead. That is real and it is difficult to replicate by hand once you care about more than a handful of prompts.
What they do less well, and what the marketing tends to blur, is causation. Nobody outside OpenAI, Google, Anthropic and Perplexity can observe how retrieval and ranking actually work inside those systems. Every optimization recommendation in this category is therefore inference from correlation. The good vendors say so, and the entries here record which ones do.
There is one methodological question that separates these tools more sharply than any feature comparison, and it is worth asking on every sales call: how many times is each prompt sampled? Language models are nondeterministic, so asking once and reporting the result is measuring noise. Asking repeatedly and reporting a distribution is measurement. Vendors who have thought about this will answer immediately.
The last thing to know before shopping is commercial rather than technical. Most tools in this category do not publish pricing, which makes comparison expensive in a way that favours vendors over buyers. Where a tool does publish, we say so, because in this category it is a genuine differentiator.
Headline prices are rarely comparable, because vendors here charge for different things. These are the models you will meet and what each one hides.
No pricing page. You book a demo and receive a proposal shaped by your company size.
Watch for: This is the default in this category, and it means you cannot compare two vendors without entering two sales cycles. Ask for the number on the first call and treat reluctance as information.
You buy a monthly allowance of model responses. Each prompt sampled against each engine consumes credits.
Watch for: The only model in this category that lets you calculate cost in advance. Multiply prompts by engines by refresh frequency before comparing it to a quote-only competitor.
Plans are separated by how many brands or domains you track and how many people can log in.
Watch for: Agencies scale on projects, not people. A plan generous with seats and stingy with projects is the wrong shape for an agency and the right shape for an in-house team.
"Evaluate output quality" is not a test. These are specific things to do while you still have a free trial, and what each outcome actually means.
What it tells you: Large language models are nondeterministic. A tool sampling once is reporting noise as a trend; a tool sampling many times is measuring a distribution. This single question separates the category more cleanly than any feature list.
What it tells you: Tells you whether the tool's picture of reality matches yours before you start making decisions from its picture of everything else.
What it tells you: This field is roughly two years old. Honest vendors will describe correlation and reasoning; a vendor claiming proven causation is overselling what anyone currently knows.
What it tells you: Knowing which publications an engine trusts for your category is actionable. Knowing only your own score is a dashboard metric with nowhere to go.
What it tells you: Time series is the whole value here. A tool that takes the history back on cancellation has locked you in by design.
Some of this job is already covered by tools you pay for or can use free. Worth ruling out before adding a subscription.
They describe overlapping work with different emphases. SEO targets ranked links. AEO, answer engine optimization, targets being the cited source inside a generated answer. GEO, generative engine optimization, is used interchangeably with AEO by most vendors. Treat the three acronyms as marketing distinctions rather than separate disciplines, because the underlying work is largely the same: be genuinely authoritative on a topic and be technically retrievable.
Measurement is the part that works. Every tool here can tell you whether you are being cited and by which engine. The optimization half is much younger and largely reasoning from correlation, because nobody outside the model providers can observe the retrieval and ranking directly. Buy for measurement, treat recommendations as hypotheses.
The category is young, enterprise-led and moving fast, so vendors are still discovering what the market will pay. That is a reason, not an excuse. It means you cannot compare shortlisted tools without booking demos, and it disadvantages smaller teams who lack the time to run three sales conversations.
If AI answers are already sending you traffic or removing it, yes, because you cannot manage what you cannot see. If you are asking on principle rather than from evidence, spend a month checking your top prompts by hand first. That costs nothing and tells you whether the problem is real for your business.
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