What tool can alert me when AI says something false about my business?

The tool you want is an AI visibility monitor that runs your buyer questions through each AI engine on a schedule. It extracts the claims each answer makes about you and checks them against facts you have confirmed. When a claim contradicts a fact, it raises an alert.

The fact sheet is the part most people skip. Without it, a tool can tell you that ChatGPT mentioned you. It cannot tell you that ChatGPT got your price wrong. "Wrong" needs a reference point, and only you can supply it.

A useful fact sheet covers the claims buyers act on:

• Pricing tiers and what each includes
• Product names, current and retired
• Founding year, headquarters and ownership
• Integrations and certifications
• What you do not offer (a common source of invented features)

Keep it short and current. A stale fact sheet produces false alarms, because the tool flags the AI for disagreeing with your old price. If you want to test accuracy by hand first, see how to tell whether ChatGPT is accurate about your company.

Not every error deserves the same alarm. An AI saying you were acquired when you weren't can cost a deal. An AI getting your headcount slightly wrong rarely will.

A good alert assigns a severity level, such as critical, moderate or minor. Be aware that this weighting is a product choice, not research consensus. FActScore, a widely used factuality benchmark, treats every atomic fact as equally important. Tools add severity because buyers need to know what to fix first.

What to look for in the alert itself:

• The exact claim, quoted from the answer
• Your fact it contradicts
• The severity, with critical errors at the top
• The question that produced it, so you can reproduce it

Also check how the tool rolls errors into a score. A score that simply subtracts penalty points will fall as you add more questions, even when accuracy is unchanged. A sound score divides errors by answers returned, so the same error rate scores the same at 20 answers or 400.

Some AI claims are provably wrong. Others just can't be checked. Say an AI states your employee count and your fact sheet has no headcount. The tool cannot call that false. It can only say it has no record.

The research does not settle how to score this. FActScore lumps "contradicts" and "lacks evidence" into one not-supported class. That is fine for a benchmark. For an alert, it is misleading: an unverifiable claim may be true.

A good alert separates the two:

• False: the claim contradicts a fact you supplied. Act on it.
• Unverifiable: no matching fact exists. Either add the fact to your sheet or ignore it.

Unverifiable flags are also a prompt to expand your fact sheet. Each one marks a topic buyers ask about that you haven't documented. It also helps to know whether an error is invented or simply old; the difference between a hallucination and an outdated answer changes the fix.

"AI" is not one system. Google says AI Overviews and AI Mode "may use different models and techniques" and can return different links. ChatGPT, Perplexity and Claude each retrieve from different sources, and each decides per question whether to search the web at all.

Knowledge cutoffs differ too. As of October 2026, OpenAI lists a February 16, 2026 cutoff for its GPT-5.6 models and August 31, 2025 for its Instant path. An answer given without live search can repeat facts that were true a year ago.

This is why a single blended accuracy score hides problems. In a 2026 experiment by OtterlyAI, Microsoft Copilot produced 69% of one site's tracked AI citations while four other engines barely cited it. An average would have masked the gap.

Your alerts should name the engine and, where possible, whether the answer cited web sources. Treat a result built on very few answers with caution. One flag on two returned answers looks like a collapse when it is really a thin sample. Errors from an engine that failed to answer should not count as clean answers either.

Set up monitoring in this order:

1. Write your fact sheet. Ten to twenty facts buyers act on, each with one correct value.
2. Pick three to ten buyer questions. Use the questions prospects actually ask, not your brand name alone.
3. Run a baseline across engines. Note which engine says what, and whether each answer searched the web.
4. Schedule repeat checks. Monthly works for most small businesses. See affordable ways to monitor AI chatbots.
5. Fix the source, then recheck. State the correct fact plainly on a page crawlers can fetch, in the HTML before JavaScript runs.

Alerts on answers are half the job. If an AI crawler is blocked, the engine can't read your correction. Alerts for AI crawler access regressions cover that side.

No tool controls what a model says. Publishing a clear, fetchable fact gives an engine a sentence it can quote, but stopping AI from making things up is not fully in anyone's control. For a quick snapshot before committing, the free checker on this site runs up to three buyer questions. For scheduled audits that flag wrong facts across five engines, 99Visibility's paid plans start at $49 a month.