How to check and fix what AI says about your brand

To check whether AI describes your brand correctly, start with the facts that matter. Ask ChatGPT, Perplexity and Google the questions your buyers ask in each market, and compare every claim in the answers with those facts. Then trace each wrong claim to the sources the engine cited and fix those sources. Tools such as Asky now run these AI brand accuracy checks for you, and seven of them are compared below.

The problem is common. In a study of more than 3,000 answers from ChatGPT, Copilot, Gemini and Perplexity, journalists found a significant issue in 45% of them (EBU). That study covered news, not brands, but it shows how often fluent, confident answers carry errors.

Why does ChatGPT get facts about your company wrong?

AI engines repeat what their sources say, and many of those sources are not yours. When a review site still lists last year's prices or a directory describes a discontinued product, the engine can repeat it with confidence.

Five causes come up again and again:

• Outdated third-party pages. Reviews, roundups and directories that were right when written but never updated.
• Missing facts on your own site. If your pricing or product limits are not stated clearly, engines fill the gap from elsewhere.
• Conflicting pages. Old landing pages, regional sites or translations that say something different from your main pages.
• Training data. Models learn from older snapshots of the web, so a change you made recently may not have reached them.
• Name confusion. A company with a similar name can be blended into answers about yours.

So the fix starts with those sources, beginning with your own pages, as the steps below show. Your buyers notice some of these errors and miss others. Among people in Germany who use AI to search, 42% say they have received false or made-up information, yet only 57% check AI answers before using them (Bitkom).

What does an inaccurate AI answer cost in pipeline, churn and support?

Inaccurate AI answers cost pipeline, because buyers rule you out before they reach your site. They also add churn and support load when customers buy on a promise you never made. The cost is hard to see, because it starts in conversations you never take part in.

Buyers already lean on these answers. In a Gartner survey of 645 B2B buyers, 45% said they used generative AI during a recent purchase. And 69% prefer to validate AI-generated insights with sales reps (Gartner). Every wrong price or missing feature becomes a question your sales team has to answer, if the buyer asks at all.

What is the difference between brand sentiment and brand accuracy?

Sentiment measures the tone of an answer; accuracy measures whether its facts are true. An answer can praise your product warmly while quoting the wrong price, or describe you in plain terms and get every fact right.

Most AI visibility tools report sentiment. Fewer check accuracy, because it requires a source of truth: the facts you want engines to state. Track both, and read our guide to AI sentiment monitoring for the tone side.

How do you check AI answers about your brand by hand?

You can run a first check in an afternoon. It will not scale, but it shows how big the problem is.

1. Write down 10 to 20 facts that matter to buyers: prices, plans, key features, limits, markets you serve and policies.
2. Turn each fact into the questions buyers ask, both direct ("How much does it cost?") and open ("What is it best for?").
3. Ask each question in ChatGPT, Perplexity and Google, from each country and in each language you sell in.
4. Mark every claim about your brand as correct, partly correct or wrong against your facts.
5. For each wrong claim, note the sources the engine cited next to it.
6. Repeat the same questions after each fix, so you can see whether the answer changed.

The limits show quickly: answers change from day to day, differ by engine and country, and a spreadsheet cannot keep up. Tools automate most of these steps, as the comparison below shows.

How do you fix brand misinformation in AI answers?

Fix the sources, not the answer. Engines rebuild answers from what they read, so correcting what they read is the durable fix.

• Update your own pages first. State the correct fact plainly on the pricing, policy, product or FAQ pages engines are most likely to read, and keep it consistent across languages.
• Correct third-party sources. Ask review sites, directories and publishers to update outdated claims, starting with the pages engines cite most.
• Publish what is missing. If engines guess because a fact is not stated anywhere, add a clear page or section that states it.
• Retire conflicting pages. Redirect or update old pages that still carry the wrong version, and say plainly when a product is discontinued and what replaced it.
• Report clear errors. ChatGPT, Perplexity and Google all let you flag a wrong answer, which is worth doing, but it does not replace fixing the source.

Then measure again. A fix only counts when the answers change, so keep checking the same facts in the same markets. Citations show which sources to fix first; our guide to AI citation tracking explains how to read them.

How often should you check AI answers about your brand?

Check after every change buyers care about, and on a regular schedule in between. A price change, a product launch, a rebrand or a new market are the moments when old answers do the most damage.

• After a change. Re-check the affected facts once your pages are updated, then again a few weeks later, because engines pick up new sources at different speeds.
• On a schedule. Run the full fact set regularly, so new errors from third-party pages surface before buyers repeat them to your sales team.
• Per market. Check each country and language on its own, because a fix in English does not reach a German answer that cites German sources.

Teams selling across Europe should plan for this from the start; our guide to AI visibility tools for European companies covers language coverage.

Which tools check whether AI answers about your brand are correct?

Asky, Peec AI, Profound, Scrunch, AthenaHQ, MaxAEO and Semrush all check AI answers about your brand, from per-claim verdicts to manual review. We included seven tools that buyers compare for this job and whose own pages describe checking AI answers against brand facts or reviewing them by hand. We compared them on four checks, using each vendor's own pages in October 2026.

Of the seven, only Asky's public pages describe writing its own questions for each fact and asking them in the markets chosen for that fact. Asky also compares each engine's answers with a positioning statement you set. For the wider market, see our list of the best AI visibility tools in 2026 and our AI visibility tool pricing guide.

Finseo offers a fact check as an add-on on every plan, and Ahrefs offers checks through Letaido, a separate product. Otterly.AI and ZipTie show full answers with their cited sources. ZipTie leaves the accuracy judgment to you, and Otterly.AI offers a beta prompt that fact-checks answers in Claude through its connector.

1. Asky: best for checking each fact per market and fixing pages

Overview

Asky's brand alignment checks what AI engines say about your brand against the facts you set, one fact and one market at a time. It is part of Asky, the AI-native SEO and GEO platform that closes the loop from insight to execution. When a claim is wrong, the same platform helps you fix it: refresh a page, work on the third-party sources engines cite or publish the missing fact.

Strengths

• You list the facts that matter and choose, for each fact, the markets (country and language) to check it in. Asky writes the questions and asks them on each engine you monitor.
• It also checks a sample of the answers your tracked prompts collect when they mention your brand, so everyday answers count, not only test questions.
• Each wrong statement is marked Contradicts or Partly contradicts against a fact, with the exact quote and, where the engine cited one, the source cited for that statement.
• Asky compares how each engine describes you with your positioning statement, tracks perception attributes with sentiment, and shows how each fact changes over time.
• Content refreshes publish corrected pages to Webflow, WordPress or Sanity, changing only the field or block that needs it.

Weaknesses

• Facts count per market, so many facts in many countries use more of your allowance.
• It is built as part of a full SEO and GEO platform, not sold as a standalone accuracy checker.

Best for

Teams that sell in several markets and want accuracy problems found, traced and fixed in one place. See how Asky's brand alignment works.

2. Peec AI: best for fact checks inside daily tracking

Overview

Berlin-based Peec AI includes fact checking in its brand perception features. You enter brand facts, and Peec extracts claims from tracked answers and gives each one a verdict.

Strengths

• Each claim shows the answer passage, prompt, model and source pages.
• Fact checks are included from the $95 Starter plan (€85 in Europe), with daily tracking.
• From the Pro plan, Objections show arguments engines raise against your brand, traced to source pages.

Weaknesses

• Starter checks 5 facts against answers from 5 tracked prompts, and Pro 20 facts against 10 prompts, so larger fact sets need a bigger plan.

Best for

Teams that want fact checks inside the daily tracking they already run. See our Peec AI comparison.

3. Profound: best for enterprise teams with a knowledge base

Overview

Profound's FactCheck extracts factual claims AI makes about your brand and checks each against a knowledge base you maintain, classifying claims as accurate or inaccurate.

Strengths

• An accuracy score, with claims clustered by theme.
• Each inaccurate claim is traced to the citation URL behind it.
• Agents can draft page updates, new content or outreach to fix it.

Weaknesses

• It requires a knowledge base, first results take seven days, and brand pricing is custom.

Best for

Enterprise brands with an existing knowledge base and an enterprise budget. Read our Profound comparison.

4. Scrunch: best for Enterprise customers testing fact checks

Overview

Scrunch's Knowledge Studio includes a Fact Check Agent that compares what AI agents understand about your company with approved company knowledge to flag factual errors.

Strengths

• Fact checks sit next to AEO audits and agent traffic data.
• Approved company knowledge becomes the reference point.
• A Conflict Agent flags conflicting information on your own websites.

Weaknesses

• The Fact Check Agent is a beta on the Enterprise plan.

Best for

Existing Scrunch Enterprise customers.

5. AthenaHQ: best for knowledge-base claim review

Overview

AthenaHQ's Oracle compares AI responses with verified facts in your knowledge base and flags confirmed inaccuracies.

Strengths

• Each inaccuracy shows the AI claim next to the known fact, why it was flagged and possible sources.
• It also flags disagreements between models and possible issues in your knowledge base.
• Claim review sits alongside tracking and content publishing.

Weaknesses

• Oracle is listed on the Enterprise plan and needs at least 25 verified facts before the first scan.

Best for

AthenaHQ Enterprise customers who manage a knowledge base.

6. MaxAEO: best for a low-cost first look

Overview

MaxAEO's AI Understanding module checks AI answers against the brand knowledge you enter and shows a fact accuracy gauge.

Strengths

• The gauge shows the share of AI statements that match your facts.
• An information gap list puts the AI's wording next to your real information, with counts and platforms.
• Every plan includes every feature, from $19 a month, with a 7-day trial.

Weaknesses

• Accuracy is judged against the brand description and profile fields you enter, so results depend on how complete they are.

Best for

Small teams that want a quick, low-cost read on accuracy.

7. Semrush: best for manual review inside an SEO suite

Overview

Semrush shows how AI describes your brand in its AI Visibility Toolkit, and you judge accuracy by reading the answers, perception descriptions and the sources in Narrative Drivers.

Strengths

• Brand descriptions and cited sources next to Semrush's SEO data.
• Brand performance reports per location and language for each tracked domain.
• In Enterprise AIO, Fact Check Analysis lists the URLs carrying a false claim, with the exact quotation from each.

Weaknesses

• The toolkit does not give claims an automated verdict.

Best for

SEO teams on Semrush, with automated fact checks for Enterprise AIO customers. Our Semrush comparison has more.

Which tool fits your situation?

Match the tool to the problem you are trying to solve.

• You repositioned, or want to see how each engine positions you. Asky compares each engine's answers with the positioning statement you set and shows per fact how they change over time. Semrush's perception reports show the descriptions engines use, which you compare by hand.
• Your tool only gives you a sentiment score. Asky, Peec AI and Profound add a verdict per claim against facts you set, and Asky keeps perception attributes with sentiment alongside it.
• An agency checks answers by hand today. Asky automates the manual steps above: you list the facts and markets, and it writes the questions, asks them on each engine you monitor and marks each wrong statement.
• Engines repeat wrong prices or policies. Asky flags each contradicting statement with the source cited for it, and its content refreshes update your pricing or policy page in Webflow, WordPress or Sanity. Profound's agents draft page updates and outreach.

Where should you start?

Pick the ten facts that would cost you most if AI got them wrong, and check them this week in your two biggest markets. Fix the sources behind any wrong claims, then put the checks on a schedule so you see new errors before your buyers do.