AI Reputation Management:Fix What AI Says About You

Because these models build answers from sources across the open web, plus what they learned in training. If the web contains an outdated article, a false review, a data-broker profile, or a case of mistaken identity with someone who shares your name, the AI can repeat it, sometimes stated confidently and without the nuance a human would add. The fix is to correct the underlying sources, not to argue with the model.

Partially, through official channels. OpenAI provides a Privacy Portal where you can request that certain personal information stop appearing in ChatGPT's responses when it's inaccurate or inappropriate. Requests are reviewed case by case. Importantly, that removal does not delete the information from the external websites or search engines it came from, so real, lasting change also requires addressing those sources, which is what we do.

No one can directly edit an AI model's output, and we won't pretend otherwise. What we can do, and what actually works, is change the sources the model reads from: removing or suppressing false content, strengthening accurate authoritative sources, and reinforcing your verified entity data. As the models re-read the web, their answers move with the sources.

We fix a brand's reputation in AI answers by changing the sources those answers are built from, because you can't edit the model itself. First we audit what ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews currently say about your company and trace every claim to its cited source. Then we remove or suppress the false and damaging sources, strengthen accurate authoritative content, and reinforce your verified entity data (the work behind Generative Engine Optimization). As the engines re-read the web, the answer catches up. It's not instant: results tend to appear over weeks to months as models refresh and re-crawl, and we monitor each engine until the corrected answer holds.

Often, yes, though not by editing the AI directly. An AI hallucination is a confidently stated claim that isn't true, sometimes invented, sometimes a mix-up with a same-named person or company. Because these models assemble answers from web sources (and, for false personal data, through OpenAI's personal-data-removal request), the practical fix is source-level: we remove or suppress the pages feeding the false claim, publish and strengthen accurate authoritative content the models can cite instead, and correct your entity data so the correct facts are the easiest ones to find. No one can guarantee an instant edit to a model's output, so changes appear as the engines re-read the web, usually over weeks to months, and we keep monitoring until the hallucination stops being repeated.

Because those threads rank well in Search and read as candid, real-user opinion, so AI engines surface and cite them heavily, and Google now features Reddit prominently in its results. The practical effect is that a single prominent thread, accurate or not, can anchor the AI's answer about you. We treat forums like any other source: we engage or correct where it's legitimate to do so, strengthen the accurate authoritative content around them, and address genuinely false or policy-violating posts through each platform's own process.

Indirectly, and honestly. When someone asks "[company] alternatives" or "is [company] better than X," the engine assembles that comparison from third-party sources: reviews, listicle articles, forum threads, and your own pages. We can't dictate the model's verdict, and we won't claim to. What we can do is correct false claims feeding the comparison, strengthen accurate authoritative content about what your company actually does well, and fix your entity data, so the sources the engine reads are accurate rather than outdated or wrong.

GEO is the practice of optimizing content and entity signals so generative AI engines represent you accurately and favorably. The term comes from a 2023 research paper (accepted to KDD 2024) that formalized how content can be structured to improve visibility in AI-generated answers. In a reputation context, GEO is one tool we use alongside removal and suppression, not a magic switch.

Google says its AI features are rooted in its core Search ranking systems, a page has to be indexed and eligible to rank in Search to feed an AI Overview. So fixing an AI Overview means changing what ranks in Search for your business: removing or suppressing the damaging source, and strengthening accurate content so that's what Google surfaces and summarizes.

A GEO or SEO agency generally tries to rank brands more prominently inside AI answers for marketing. We do reputation defense: finding and fixing what AI gets wrong or negative about you. The techniques overlap (both change sources), but the goal, and the focus on removing false and damaging content, is different.

It varies. Once a source is removed or suppressed and Search re-crawls it, some AI answers update within weeks; others lag because models have a training cutoff and refresh on their own schedule. We monitor continuously and re-check each engine rather than assume a one-time fix holds. We'll give you an honest timeline for your situation.

That's a fast-evolving area, and we're not attorneys, so this isn't legal advice. So far, early U.S. cases have largely gone in the AI companies' favor (for example, Walters v. OpenAI was dismissed in 2025), which is part of why we focus on the practical path: correcting the sources so the false statement stops being generated. If your situation may warrant legal action, we'll say so and can coordinate with counsel.

Start with our free AI reputation audit. We prompt ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews the way real people would ask about you or your business, document what each says, and trace the sources behind it, so you know exactly what's out there before deciding anything.

Yes. Individuals usually come to us about a false or damaging statement AI repeats about them personally; businesses come about what AI tells buyers, investors, and candidates. The method is the same, audit, trace sources, correct, monitor, and for companies we tie it into a broader corporate reputation program.

Ask it directly, the way a real person would: "Who is [your name]?", "Is [your company] legit?", "What are [your company]'s alternatives?", and "What is [your name] known for?", and do it in ChatGPT, Gemini, Perplexity, and Google's AI Overviews, since each answers differently. Note what's wrong and, where the tool shows sources, which pages it's citing. Our free audit does this systematically across every major engine and traces each claim back to its source.

Two reasons. First, models have a training cutoff, so a base answer can reflect an older snapshot of the web. Second, even when a model searches live, it pulls from whatever still ranks and is indexed, so an outdated article or profile that's still live keeps feeding the answer. The fix is to update or remove those source pages and strengthen current, accurate ones; as the model re-reads the web, the answer catches up.

They overlap but aren't identical. GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) are mostly marketing disciplines focused on getting a brand mentioned more prominently in AI answers. AI reputation management is defense-focused: finding and fixing what AI gets wrong or negative about you. We use GEO/AEO techniques (they both work by shaping sources and entity signals), but the goal, and the emphasis on removing false and damaging content, is different.

Indirectly, yes. Google says its AI Overviews are grounded in its core Search ranking systems, a page has to be indexed and eligible to rank in Search to feed an Overview. So we change what ranks: removing or suppressing the damaging source and strengthening accurate content, which changes what Google surfaces and summarizes. No one can edit the Overview directly, but shifting the underlying sources is what moves it.

It depends on scope, whether it's an individual or a business, how many engines and sources are involved, and how much removal versus source-building is needed. It starts with a free audit, and any content removals are billed only after they're confirmed, no upfront fee for those. We scope the rest transparently before you commit.