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Free AI Hallucination Check for Your Brand

99Visibility Research · Updated October 21, 2026 · 7 min read

Short answer

A free AI hallucination check compares what AI assistants say about your brand against a short list of facts you have verified. Each claim is sorted into one of four groups: correct, wrong, unverifiable or missing. You can run it by hand in about an hour. It shows which errors come from a model's frozen training data and which come from pages it retrieved, and the fix differs for each.

Key takeaways

  • Start with 10 to 15 verified facts, each with the URL where you publish it, before you ask any AI a single question.
  • Separate claims that contradict a verified fact from claims you simply have no record of, because only the first group is proven wrong.
  • Run each question with web search off and on: an error that appears only without search points to old training data, while an error with citations points to a page you can trace.
  • Retrieval errors are fixable at the source, while errors that come from training data alone cannot be changed by anything you do this quarter.
  • A single check is a snapshot, so record the date, the surface and whether the answer showed citations.

What a free hallucination check tells you

A hallucination check answers one narrow question: when an AI assistant describes your company, which statements match the facts? It does not tell you whether you are visible or how often you are named. It tells you what is wrong and where the error probably came from.

That second part matters most. The same wrong price can come from two places. It can come from the model's training data, which is frozen at a cutoff date. It can also come from a page the assistant fetched while answering. The fixes are different, so the check has to separate them. Our guide to hallucinated versus outdated AI answers covers that diagnosis in more depth.

Build your verified fact list first

You can't call an answer wrong without a reference. Write the list before you open any chatbot.

Keep it short and specific. Ten to fifteen facts is enough. Good candidates:

  • Current prices and plan names
  • Founding year, headquarters city and ownership
  • Product names, including any you have retired
  • Key integrations and certifications
  • One-line description of what you do and who it serves

For each fact, record three things: the exact wording, the URL where you publish it, and the date you last confirmed it. Then give each fact a severity. A wrong owner or a wrong price is critical. A wrong headcount is minor. This weighting is a practical judgement, not a standard: the FActScore benchmark gives every fact equal weight.

Finally, check your own site for contradictions. If your pricing page, footer and about page state the same fact differently, an assistant may repeat any of them. Fix those first.

How to run the check by hand

  1. Confirm your facts are in the raw HTML. Many AI crawlers download JavaScript but do not run it. Vercel found that ChatGPT and Claude crawlers "can't read client-side rendered content". Fetch the page without a browser and search for the fact:
curl -s https://example.com/pricing | grep -i "per month"

If the price only shows up in a browser, crawlers that skip JavaScript never see it.

  1. Check crawler access. Open yoursite.com/robots.txt. Look for rules on OAI-SearchBot (ChatGPT search), PerplexityBot and Claude-SearchBot. OpenAI states its bot settings are independent, so blocking GPTBot only affects training.

  2. Use a clean session. Log out, or turn memory off. OpenAI says ChatGPT may use saved memories when rewriting a search query, which makes results hard to repeat.

  3. Ask each question twice. Once with web search off, once with it on. Use plain buyer questions: "What does [brand] cost?", "Who owns [brand]?", "What does [brand] do?"

  4. Record everything. Save the answer text, the date, the surface (Gemini app, Google AI Overviews and AI Mode are different products), and every cited URL.

  5. Score each claim against your list using the categories below.

How to read the result

Sort every factual claim in each answer into one group.

Result What it means Next move
Correct Matches a verified fact Note it and move on
Wrong Contradicts a fact on your list Trace the source
Unverifiable You have no fact on record to check it Add the fact to your list or ignore it
Missing A key fact never appears Check access and rendering

Keep "wrong" and "unverifiable" apart. An assistant claiming you have 200 staff when you never published a headcount is not proven false. It is a gap in your list. Academic benchmarks blur this line: FActScore's "not supported" label covers both contradicted and unevidenced claims. For your purposes, only contradictions are errors.

Then diagnose each wrong claim:

  • Wrong with search off, and the fact changed after the model's cutoff: probably outdated training data. As of October 2026, OpenAI lists a February 16, 2026 cutoff for its GPT-5.6 models and August 31, 2025 for the Instant path ChatGPT uses.
  • Wrong with search on, with citations: a retrieval error. Open the cited pages. One of them usually states the wrong fact.
  • Wrong with search on, no citations: you can't tell which. Note it and retest.

The hallucination triage playbook walks through ranking these by severity.

What each fix involves

Retrieval errors are the ones you can act on. If the cited page is yours, correct it and make sure the fact is in the server-rendered HTML. A specific fact stated plainly on a fetchable page gives the engine a sentence it can quote. If the cited page belongs to someone else, such as an old review or directory listing, ask that site to update it. When engines cite other sites instead of yours, those pages are the route into the answer.

Access problems look like missing or stale facts. Fix robots.txt for the search bots, then confirm your CDN or firewall doesn't return a 403 to them. A crawler that robots.txt allows can still be blocked at the network layer.

Outdated training data is the hard case. Nothing you publish today reaches an answer given with search off. The fix is making sure the correct fact is reachable for answers that do search, and waiting for a later model. You can also report errors to vendors; see whether OpenAI or Google will correct your company's information.

No fix guarantees the next answer is right. You control what engines can read. You don't control what they say.

Limits of any free check

A hand check is a sample. Keep these limits in mind:

  • Answers vary. The same question can produce different answers minutes apart.
  • Retrieval is discretionary. ChatGPT decides per query whether to search. Without visible citations, you don't know which kind of answer you got.
  • Cited is not the same as used. OpenAI exposes more retrieved sources than it cites, so the citation list is incomplete.
  • Google has several surfaces. Google says AI Overviews and AI Mode "may use different models and techniques". Check them separately; see checking AI Overview accuracy.
  • No tool sees real user prompts. Your questions stand in for what buyers type.

Prices are the most common critical error. The free pricing accuracy check focuses on that one fact type.

The faster route

Running six questions across several assistants by hand takes time, and keeping the records consistent is the tedious part. The free checker on this site runs up to three buyer questions, yours or ones written from your homepage, and scores the answers in one pass. It is a snapshot, not ongoing tracking.

For a check you can repeat from a standalone page, the AI Visibility Checker runs the same kind of test. Either way, keep your verified fact list. It is what turns an answer into a finding. If ChatGPT is the main problem, the guide on ChatGPT having wrong information about your business covers platform-specific steps.

Frequently asked questions

What counts as an AI hallucination about my brand?

For a brand check, a hallucination is a specific claim that contradicts a fact you have verified and published, such as a wrong price, owner or product name. A claim you have no record of, like an invented headcount, is unverifiable rather than proven wrong. Treat the two differently: fix the first at its source, and decide whether the second matters enough to publish the correct fact yourself.

How can I tell if an AI answer used web search?

Look for citations or source links in the answer. If they appear, the assistant retrieved pages while answering, and you can open each one to find the wrong fact. If none appear, the answer may have come from training data alone, or the surface may simply hide sources. In that case you can't be sure, so turn search on explicitly where the product allows it and ask again.

Will fixing my website correct what ChatGPT says?

It can correct answers that search the web, provided ChatGPT's search crawler can reach the page and the fact is in the HTML before JavaScript runs. It will not change answers given without search, because those come from training data frozen at a cutoff. No change on your site guarantees a specific answer. It removes the blocks that stop a correct fact from being read.

How often should I rerun a hallucination check?

Rerun it whenever a key fact changes, such as a price increase, rebrand or acquisition, and after any site rebuild that could change rendering. Between those events, a monthly check is a reasonable rhythm for most brands. Always record the date and surface, because assistants change models and defaults, and a result from three months ago may describe a system that no longer exists.

Does adding schema markup stop AI from getting my facts wrong?

There is no evidence it does. Google says structured data isn't required for its generative AI features, and an Ahrefs matched test found AI Overview citations fell 4.6% after pages added schema. Existing markup does no harm. The steps with evidence behind them are making the fact visible in server-rendered HTML, keeping it consistent across your site, and letting the search crawlers reach it.

Sources

  1. The rise of the AI crawler - Vercel
  2. Overview of OpenAI Crawlers
  3. Searching the web with ChatGPT
  4. AI Features and Your Website
  5. [2305.14251] FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
  6. We Tracked 1,885 Pages Adding Schema. AI Citations Barely Moved.

This page is AI-assisted. It was written from a verified evidence base and checked against our editorial policy. Engine behaviour changes often; facts are as of October 21, 2026.

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