AI visibility audit tools without a credit card in the US

Search for a free AI visibility checker and you get two very different products under the same label. Some ask a model about your sector and look for your brand in the answer. Others read your robots.txt and llms.txt and tell you whether GPTBot is allowed in. Both are useful. Only the first tells you whether ChatGPT recommends you.

Below are the tools that run without a card, checked against their own pages on 25 July 2026, split by what they actually measure. Then the workflow to turn them into a report you can hand to a client, and a template you can copy.

Free tools that measure real AI mentions

These query one or more models and look for your brand in the response. That is the number you care about.

Bee LLM is our own product, so weigh that accordingly. The relevant fact for this page is the requirement, not the pitch: the five-engine result appears with no signup and no card, and the fuller report only asks for an email.

Free tools that check access, not mentions

This second family never asks a model anything. It inspects your site and tells you whether AI crawlers can reach it. A perfect score here is compatible with zero mentions in every model.

Run one of these first anyway. If GPTBot is blocked or your pages need JavaScript to render their main content, you have found the cause of a bad mention rate before spending an hour measuring it.

The official free source, and what it will not tell you

Google shipped a standalone AI performance report in Search Console on 3 June 2026. It is free, it is first-party data, and it is narrower than most write-ups suggest.

It reports impressions, pages, countries and devices. It does not report clicks, CTR, average position or query-level data, and it groups AI Overviews, AI Mode and AI Overviews in Discover into a single bucket with no split between them. Rollout started with a subset of UK site owners before going wider, so a US property may not have the report yet. Use it to size AI-surface exposure over time. Do not use it to claim a specific AI Mode number.

What to measure, and the criteria that matter

Before picking a tool, decide what the report has to answer. For a US audit without payment, five criteria separate a usable free tool from a lead magnet.

1. Access without payment details, including at the point where the result is revealed. Several tools are free to run and gated at the download.
2. Engine coverage that matches your audience. ChatGPT and AI Overviews carry most US volume, but Perplexity and Copilot matter in some categories and are missing from several free checks.
3. Traceability. Can you see the raw answer the tool scored, or only the score? Without the answer text you cannot verify a mention or check a false positive.
4. Result consistency. Run the same prompt twice. AI answers vary between runs, so a tool that reports a single number without any indication of variance is overstating precision.
5. Export. If you cannot get the data out, you cannot build the report or compare next month.

The metrics themselves are the same ones a paid tracker uses: mention rate, share of voice against named competitors, position within the answer, sentiment, and which sources the model cited. We cover how each is defined in AI search visibility metrics and KPIs.

How to run the audit end to end

This is the part no free tool does for you, and it is where the report gets its value.

1. Build the prompt set. Twenty prompts is enough for a first audit. Write them as a customer would ask, not as keywords: the query is a question, not a phrase. Cover four intents, with five prompts each: category discovery, comparison against a named competitor, a specific use case, and a purchase or hiring question. Keep them in US English if the audit is for a US market, because the same question in another language returns different brands.
2. Fix the variables before you run anything. Country, language, and whether you are logged in. Record them. An audit run from a logged-in account with memory enabled is not reproducible.
3. Run each prompt in at least two places. One free tool and one model directly. Paste the prompt into the model with no follow-up and no context.
4. Capture the raw answer, not the impression. Save the full text and the cited links for every run. This is your evidence, and it is what lets you show a client the exact sentence where a competitor appears and they do not.
5. Extract four signals per answer: does your brand appear at all, in what position relative to other brands, in what tone, and is your domain among the cited sources. A brand mentioned with no link and a domain cited with no brand mention are different problems with different fixes.
6. Repeat once. Run the whole set a second time on a different day and record both. The gap between the two runs is the honest error bar on every number in your report.
7. Consolidate. Count mention rate as answers containing your brand divided by total answers, per engine and overall. Do the same for each competitor to get share of voice.

Two runs of twenty prompts across two engines is 80 answers. Budget three to four hours by hand. That is the real price of the free version, and it is why continuous tracking is a product rather than a spreadsheet.

Report template you can reuse

Copy this structure. It maps to what a marketing lead needs to approve a decision.

1. Scope and method. Date, market, language, engines, number of prompts, number of runs, whether sessions were logged out. One paragraph, and it is what makes the report defensible.
2. Headline result. Mention rate overall and per engine, with both runs shown side by side.
3. Share of voice. Your brand against three to five named competitors, per engine.
4. Prompt-level table. One row per prompt: engine, mentioned yes or no, position, sentiment, your domain cited yes or no.
5. Cited sources. Which domains the models leaned on for your category. Third-party listicles and review sites usually dominate, and that list is your outreach target list.
6. Gaps. The prompts where every competitor appears and you do not, ranked by how commercial the question is. This is the section that turns into work.
7. Access check. Result of the crawler and llms.txt audit, with any blocked agent called out.
8. Recommended actions. Three to five items, each tied to a specific prompt or gap above, with an owner.
9. Limitations. State the variance between runs and the fact that a snapshot is not a trend. Skipping this is how AI visibility reports lose credibility.

A worked example of section 6, for a US legal services brand: across 20 prompts, the firm appeared in 2 of 40 answers, both from a single prompt naming the firm directly. Competitors appeared through a state bar directory and two review sites the firm had no profile on. The recommended action was a directory presence, not a blog post, and the audit is what showed that.

Common ways free audits go wrong

The failure is rarely the tool. It is the setup.

Prompts written as keywords return generic answers no customer would ever see. A single run reported as a trend produces a number that reverses next week and costs you the client's trust. Scoring a mention from a memory of your own brand, because you ran the prompt logged in, inflates everything. And treating a perfect crawler-access score as visibility is the most common mistake of all, because the tool that gave you the score never asked a model anything.

Questions people ask

Why do some tools ask for a card when the audit is free?

Every prompt run against a model costs the vendor money, so tools that query continuously gate their trial with a card to stop repeat signups. Tools that run one check on demand, or that only read your files, have almost no marginal cost and can leave the door open.

Can a free audit replace a paid tracker?

No, and the reason is not feature count. A free audit is one moment in time, and AI answers move between runs for the same prompt. A snapshot can tell you where you stand and whether the gap is worth work. It cannot tell you whether you are gaining or losing, which is the only question that matters once you start acting.

What if I hit a usage limit halfway through?

Finish the set by hand in the model itself and note which prompts were measured which way. A report with a documented mixed method beats a report with a hole in it.

How do I handle two tools that disagree?

Trust the raw answer you captured yourself, and record the disagreement. Tools differ in how they normalise a brand name, so a firm called with and without its legal suffix can be counted as two different brands.

Ready to write the prompt set? Start from twenty prompts to audit your brand in AI, then compare the tools that track it continuously in best AI search monitoring tools.