Correct What AI Gets Wrong About You. AI Misinformation Correction.
When ChatGPT, Gemini, or Perplexity states something false about you or your company, the fix is not to argue with the AI — it is to correct the sources the AI reads. We find them, fix them, and re-test until the answer changes.
False AI claims can usually be corrected — but not by editing the AI. ChatGPT, Gemini, Perplexity, and Google's AI Overviews build answers from sources they retrieve: Wikipedia, Wikidata, news coverage, and high-authority web pages. Correct and outweigh those sources, and the answers change — typically within two to eight weeks.
Source-Level Correction, Measured Across Six AI Systems
We do not guess at what AI says about you. We run a standardized prompt set across ChatGPT, Gemini, Perplexity, Claude, Copilot, and Google AI Overviews, capture the answers verbatim, and trace every false claim back to the source that produced it. Then we fix the source and re-test until the answer changes.
Why AI Misinformation Is Different
A false AI answer behaves nothing like a bad search result. It is harder to see, harder to argue with, and it spreads across platforms at once.
Stated as Fact
A search result is a link you can evaluate. An AI answer is a confident assertion with nothing to click and no source to argue with. The user simply believes it.
It Spreads Across Platforms
Most AI systems draw on the same small set of authoritative sources. One bad page can produce the same false claim in ChatGPT, Gemini, and Perplexity simultaneously.
It Reaches People Who Never Visit
Prospects, investors, journalists, and candidates increasingly ask AI first. They may form a view of you without ever loading your website.
It Is Invisible Unless You Test
There is no notification when an AI system starts describing you incorrectly. You only find out if someone tells you — or if you deliberately check.
The Four Kinds of AI Misinformation
Each type has a different cause and a different fix. The audit tells us which one you are dealing with.
| Type | What it looks like | Usual source |
|---|---|---|
| Fabrication | A lawsuit, fine, or controversy that never happened | Model hallucination, or a single low-quality page |
| Conflation | Your record merged with a different person or company of the same name | Ambiguous entity data; no Wikidata or Knowledge Panel disambiguation |
| Staleness | Former role, closed business, prior ownership, resolved litigation | Outdated Wikipedia, news, or directory pages still being retrieved |
| Distortion | A real event described with the wrong scale, cause, or outcome | One-sided coverage with no authoritative counterweight |
How AI Misinformation Happens — and What Can Actually Be Fixed
Modern AI systems answer questions in two different ways, and the difference decides how quickly a false claim can be corrected. Retrieval-based answers — Google AI Overviews, Perplexity, and ChatGPT when it searches — fetch live web pages and summarize them. Closed-book answers come from what the model absorbed during training, months or years earlier.
That distinction matters enormously. Correcting a retrieved source can change an answer within weeks. A claim baked into training data may persist until the model is retrained, no matter how thoroughly the original source is fixed. Any vendor who promises to delete a fact from an AI model is describing something that does not exist.
What We Can Change
We can correct and outweigh the sources AI systems retrieve: Wikipedia articles and Wikidata entries, Knowledge Panel data, news and directory listings, and the authoritative pages that models trust most. Where a platform offers a reporting pathway for false output, we use it. Where no source exists to cite, we build one — accurate, structured, and easy for a model to parse.
What We Cannot Change
We cannot edit a model, and no vendor can. We cannot guarantee specific wording, because outputs vary by session, model version, and phrasing. Claims absorbed during training can persist until retraining even after the sources are corrected. And we will not remove true information — if the claim is accurate but unflattering, that is a suppression conversation, and we will tell you so before you sign.
AI Correction Service Levels
Start by finding out what AI actually says. Escalate to correction and monitoring from there.
AI Fact Audit
Find out exactly what AI systems claim about you.
- Standardized prompt set across 6 AI systems
- Verbatim answers captured and documented
- Every false claim traced to its source
- Findings report and source map
Source Correction
Fix the sources so the answers change.
- Everything in the Audit
- Wikipedia and Wikidata correction where policy allows
- Knowledge Panel and entity-graph work
- Authoritative content and structured data
- Platform reporting where a pathway exists
- Re-tested at 30, 60, and 90 days
Ongoing AI Monitoring
Catch new false claims before they spread.
- Everything in Source Correction
- Continuous prompt monitoring
- Alerts when new false claims appear
- Quarterly re-correction
- Source-health maintenance
Our Correction Process
Measure first, trace second, fix third, verify fourth. No step is skipped.
Prompt Audit
We run a standardized prompt set across ChatGPT, Gemini, Perplexity, Claude, Copilot, and Google AI Overviews, capturing every answer verbatim along with the sources each one cites.
Source Tracing
We identify which retrievable sources are producing each false claim — and which claims have no traceable source, which tells us they are hallucinated rather than retrieved.
Correction and Counterweight
We fix what is fixable at the source, and where nothing accurate exists for a model to cite, we build authoritative, well-structured content that outweighs the bad source.
Re-Test and Monitor
We re-run the same prompt set at 30, 60, and 90 days and show you before-and-after transcripts, so you can see exactly which claims cleared and which persist.
What Is Included
Everything needed to establish what AI says about you, change it, and prove the change.
Six-System Baseline
Verbatim answers from ChatGPT, Gemini, Perplexity, Claude, Copilot, and Google AI Overviews, captured and dated.
Source Map
Every false claim traced to the page, entry, or article that produced it — or flagged as unsourced hallucination.
Wikipedia and Wikidata
Assessment of both, with correction where Wikipedia policy permits it. The most-cited sources in AI answers.
Entity-Graph Review
Knowledge Panel and entity data checked for the conflation errors that merge you with someone else.
Structured Data
Schema.org markup implemented so AI systems parse your facts correctly rather than inferring them.
30/60/90 Re-Test
Before-and-after transcripts at each interval, showing which claims cleared and which need further work.
Client Results
Two decades of correcting the record — now across AI systems as well as search.
“You will be glad to have Reputation X as a strategic partner. Their team is responsive, knowledgeable, and genuinely invested in results.”
“There is no doubt in my mind that Reputation X is the number one company for online reputation management.”
AI Misinformation FAQs
Find out what AI is saying about you.
We will run your name or brand across six AI systems and show you the answers verbatim — including anything that is wrong, and where it came from.
Request an AI Fact Audit