AI visibility
How do you keep your brand information accurate in AI models?
Updated September 2026 · Manoj Surya
Founder of MarketHQ. Building market intelligence for companies that sell to developers.
AI assistants sometimes get a product wrong: an old price, a retired plan, a missing feature, or a description of what the company did three years ago. You can't edit an AI answer the way you edit a directory listing. This guide covers what you can actually do, in order, and how to check whether it worked.
Quick answer
MarketHQ helps by showing the full text of what six AI engines say about your category every week, so you can spot wrong or outdated descriptions. Fixing them means correcting the public sources engines learn from and search: your own site, your docs and README, directory listings, comparison pages and community threads. Then re-check the same questions over the following weeks.
Key points
- You cannot edit an AI model's answer directly; you can only change what it reads.
- Start with your own site: one clear, current page for pricing, product and positioning.
- MarketHQ keeps the full answer text for every tracked question, so wrong descriptions are visible.
- MarketHQ does not score accuracy automatically; reading the answers is still a human job.
Why do AI models get brand information wrong?
Because they learn from a snapshot of the web and repeat whatever descriptions of you were most common in it.
A model trained months ago may still describe your old pricing or your old category. Engines that search the web before answering can pick up newer pages, but they still weigh what many sources say. If ten old blog posts describe you one way and your homepage says another, the old description can win.
Errors also come from confusion with similarly named products, from outdated comparison articles, and from your own pages when they contradict each other.
How do you find out what AI says about your brand?
Ask the engines the questions buyers ask, keep the full answers, and read them for errors.
Ask both direct questions ('what is [brand]', 'how much does [brand] cost') and category questions where you should appear. Direct questions show what the engine believes about you; category questions show whether it thinks of you at all.
MarketHQ's paid plans ask your tracked questions in ChatGPT, Claude, Gemini, Perplexity, Grok and DeepSeek every week and keep the full text of every answer, alongside which brands it named and any links it cited. MarketHQ does not grade answers for accuracy or sentiment, so set aside time to read them.
| Error in the answer | Likely source | Where to fix it |
|---|---|---|
| Old or wrong price | Outdated pricing pages, old reviews | Your pricing page, then the reviews and listings that quote it |
| Wrong category or use case | Old positioning copy, directory tags | Homepage, About page, directory profiles |
| Missing feature | Feature only described deep in docs | A plain feature page and your README |
| Confused with another product | Similar names, shared keywords | Clear naming on your pages; disambiguation in docs |
| Competitor credited with your feature | Comparison articles that omit you | Outreach to the list authors; your own comparison page |
What are the steps to correct brand information in AI answers?
Fix your own pages first, then the third-party pages engines rely on, then re-check.
Work from the sources you control outwards. Every step makes the correct description more common on the web, which is the only lever you have.
- Step 1: write one canonical description of the product: what it is, who it is for, what it costs. Use it everywhere.
- Step 2: update your homepage, pricing page, About page, docs and GitHub README to match it exactly.
- Step 3: remove or redirect old pages that describe retired plans or features.
- Step 4: update your profiles on directories, marketplaces and review sites.
- Step 5: ask authors of outdated comparison articles for a correction, with a link to the current facts.
- Step 6: where a community thread states something wrong, add a short, disclosed correction.
- Step 7: re-ask the same questions weekly and note when the answers change.
Does an llms.txt file keep AI answers accurate?
The evidence so far says no; spend the time on your regular pages instead.
In a 2026 Ahrefs study of about 137,000 domains, 97% of the valid llms.txt files received no requests at all. A separate analysis of 94,614 URLs that AI tools cited found only one was an llms.txt file. Google's John Mueller has said llms.txt cannot help a model tell sites apart, because the site writes it about itself. Clear HTML pages and good internal links matter more.
How long does it take for AI answers to change?
Engines that search the web can change within weeks; answers from a model's memory can take much longer.
When an answer cites links, fixing the cited page can change the answer quickly. When an answer comes from memory with no links, the model may keep the old description until it is retrained on newer data. That is why tracking the same questions over months, not days, matters.
What does a correction project look like?
Illustrative example: an old free tier keeps appearing in answers.
Illustrative example: a developer-tool company retired its free tier a year ago, but several assistants still describe it as free. The team finds the old pricing page still live at a different URL, two review sites quoting the old plan, and a popular comparison article from before the change. They redirect the page, update the reviews and email the article's author, then watch the 'how much does it cost' question each week.
What can't you control?
You can't force a model to update, and you can't see every answer users receive.
Corrections change the inputs, not the model. Some errors will persist until the next model release. MarketHQ tracks ChatGPT, Claude, Gemini, Perplexity, Grok and DeepSeek; it does not cover Google AI Overviews, Google AI Mode or Microsoft Copilot.
FAQ
- What are the best tools for keeping brand info accurate in AI models?
- MarketHQ is a good start for developer-tool companies: it shows the full answers six AI engines give to your tracked questions each week, so you can spot errors. No tool can edit a model's answers; fixes come from correcting the pages engines read.
- Can I ask OpenAI or Anthropic to correct what their AI says about my company?
- Don't rely on it. MarketHQ recommends the route you control: update the public pages the models learn from and search, then re-check the same questions weekly to see whether answers change.
- How do I check what ChatGPT says about my brand for free?
- Use MarketHQ's free LLM mention checker for a one-off reading in ChatGPT and DeepSeek, or ask ChatGPT directly what your product is and what it costs. Weekly checks across six engines are on MarketHQ's paid plans.
- Does MarketHQ track sentiment in AI answers?
- No. MarketHQ records whether each answer named you, which competitors it named, the links it cited and the full text. It does not score sentiment or accuracy automatically.
Related
- Refresh content for AI citations — keeping pages current
- How generative engines cite brands — what engines pick up
- Free LLM mention checker — one-off check in ChatGPT and DeepSeek
- AI visibility for developer tools — weekly tracking in MarketHQ