Set the Record Straight

Picture a customer who is ready to buy. They open ChatGPT or Google's AI and ask what you charge, where you are, or whether you still do the thing they need. A specific answer comes back, stated plainly and with no hedging. If that answer is wrong, if it quotes a price you retired two years ago or sends them to an address you left, they do not email you to check. They simply move on to the next name. You never see it happen, and you never learn why the phone did not ring.

That is the quiet danger of getting the facts wrong in the age of AI search. The old failure mode was being invisible. The new one is being visibly, confidently wrong. Brand Corrections exists to close that gap: to make sure that when an engine speaks about your business, it tells the truth.

Why AI gets the facts wrong

It helps to understand why this happens, because the cause points straight to the fix. AI models do not hold a live, verified record of your business. They are trained on large snapshots of the web taken at a point in time, and those snapshots go stale. If your price changed after the snapshot, the model may still be working from the old one. Retraining and refreshing happen on the provider's schedule, not yours.

On top of that, models blend many third-party sources into a single answer. Old directory listings, outdated pages on your own site, duplicate business profiles and data aggregators all feed the picture, and when those sources disagree, the model may pick the wrong one or average them into something that was never true. A single stale listing you forgot about years ago can be the reason an assistant keeps quoting the wrong hours today.

And sometimes the model simply invents a detail. When information is missing or ambiguous, a language model can generate a plausible but false fact to fill the gap, stated with the same confidence as everything else. This is often called hallucination. Nobody can put a reliable number on how often it happens for any one business, and we will not pretend to, but it is real, and it is one of the errors we look for.

What we do

Find every wrong fact

We start by asking each engine what your customers ask, in the words they use, and we do it more than once. Because these systems are probabilistic, a single run is not evidence, so we check what ChatGPT, Gemini, Perplexity, Claude, Copilot and Google's AI say across repeat runs and record where each one gets your prices, address, opening hours, services or specialism wrong. Every error is captured with a dated screenshot, so you are looking at proof rather than our word for it.

Trace each error to its source

A wrong answer is a symptom. The real work is finding what is feeding it. For every error, we trace it back to where it comes from, whether that is an outdated page on your own site, a stale directory entry, an old listing you had forgotten, a review platform profile or a record held by a data aggregator that quietly syndicates it across the web. Fixing the visible answer without fixing the source just lets the mistake grow back.

Correct it at source

Once we know where an error lives, we correct it there. We update or remove the stale pages and listings we can reach, use the correction and claim processes that platforms provide, and fix records at the aggregator level so the change flows downstream. We do not stop at deletion. We add clear, authoritative and consistent correct information across the sources engines trust, so that the next time a model learns about you, it has a better fact to learn from instead of a vacuum.

Monitor and re-check

Because models refresh on their own schedule, a correction is not a single event you can tick off and forget. We re-check the engines on a set cadence after the source fixes land, watching for the wrong answer to fade and the right one to take hold. If a corrected error resurfaces, often because another stale source we had not seen resurfaces with it, we trace and fix that too. You see the movement with dated evidence at each step.

What is honest, and what is not

Here is the line we will not cross. We can influence the sources that AI engines learn from, and we do that thoroughly. We cannot control the models themselves, and neither can anyone else. Some corrections propagate within weeks as engines refresh, others take longer, and no one can force an assistant to update on demand. Any agency that promises to flip a specific AI answer by a specific date is selling you something that does not exist.

What we can promise is the honest version: we correct every source we can reach, we make the truth easy for engines to find and consistent wherever they look, and we show you the answer before and after so you can judge the effect with your own eyes. That is the real lever, and we pull it as hard as it goes.

How this helps Google and AI at once

Correcting your facts is not only about what an assistant repeats. The same stale listings and inconsistent details that confuse a language model also weaken your standing in classic search. Search engines reward businesses whose information is consistent and correct across the web, and local trust in particular leans on matching names, addresses and details wherever they appear. When we clean up the sources feeding a wrong AI answer, we are usually tidying the exact signals that support your Google and local visibility as well. One piece of work, both halves of search improved.

What you get

The deliverable is a clear record of what was wrong, what we did about it and how the picture is changing, backed by dated evidence throughout. Nothing here rests on our say-so.

• A full sweep of what each AI engine says about you, across repeat runs
• A list of every wrong fact found, with dated before screenshots
• The traced source behind each error, named and located
• Corrections made at source across your pages, listings and profiles
• Correction and claim requests filed on third-party platforms, documented
• Clear, consistent correct information added where engines look
• Scheduled re-checks showing the wrong answers fade, with after screenshots
• A plain-English summary of what shifted, what is pending and what is out of our reach

Honest limitations

We influence sources, we do not control models, and we will never tell you otherwise. Timing varies from weeks to longer depending on how each engine refreshes, and we cannot guarantee that any specific assistant will update by any specific date, because nobody can. Some errors sit on third-party platforms whose correction processes are slow or where the owner has to act, and while we file and chase every request we can, we cannot force an outside party to move. What we do guarantee is honesty: every claim backed by a dated screenshot, and a clear account of what is fixed, what is pending and what is beyond our control. If you want the corrections implemented and re-checked every month, that is the monthly plan.

Questions people ask

Why does ChatGPT say the wrong thing about my business?

Usually because it learned from a stale or inconsistent picture of the web. Models are trained on snapshots that go out of date, and they blend information from many third-party sources. If an old directory listing, an outdated page or a duplicate profile still carries your former price or address, the model can repeat it with total confidence. Sometimes the model also invents a plausible but false detail to fill a gap. We trace which of these is happening in your case before we touch anything.

How fast can you fix a wrong AI answer?

It varies, and we will not pretend otherwise. Once we correct the underlying sources, some engines pick up the change within weeks, while others refresh on their own slower schedule. We cannot force any assistant to update on demand. What we can promise is that we correct every source we can reach, add clear and consistent correct information for engines to learn from, and re-check on a set cadence so you can see the picture move with dated evidence.

Can you force ChatGPT to update?

No, and be wary of anyone who says they can. We do not control the models, we influence the sources they learn from. We correct the listings, pages, profiles and aggregator records that feed the mistake, and we make the correct facts easy to find and consistent across the web. That is the honest lever available to anyone. We show you the answer before and after so you can judge the effect for yourself.

What if the error is on someone else's website?

That is common, and it is a large part of the work. Wrong facts often live on directories, review platforms, old listings or data aggregators rather than your own site. Where a platform has a correction or claim process, we use it on your behalf. Where a record is fed by an aggregator, we correct it at the aggregator so the fix flows downstream. We cannot guarantee a third party will act, but we document every request and chase what we can.

Sources

Every statistic here is attributed inline to the source below. We link to primary material so you can check each claim yourself. If a number is not attributed, treat it as our professional judgement rather than a measured fact.

• Ofcom, Online Nation, from apps to AI search: how the UK goes online in 2025
• Ahrefs, research on overlap between AI citations and Google rankings, 2025