Audit AI answer accuracy

Know what AI says about you, and whether it is true.

“Someone sent me a screenshot of ChatGPT saying we had been acquired. We had not.”

Every day, on every major AI engine, we run the questions a buyer, a journalist, a candidate, or a partner asks about you and your category, in each market you sell in. Then a person on our team reads the recorded answers claim by claim, marks what is wrong or outdated or missing, and traces each claim back to the source it came from. You get a report before anyone decides what to fix.

Why you cannot answer it today

One screenshot is not an audit

You know the engines are talking about you. What you do not have is a record of what each one says, in each market, and where it got it from.

  • The evidence is one screenshot

    Someone asked ChatGPT once, on their own account, and pasted the answer into Slack. Nobody knows whether the next person gets the same answer, because nobody asked twice.

  • Every engine says something different

    ChatGPT has the price wrong. Gemini has last year’s product name. Perplexity is right but cites a competitor for it. Across five engines and four markets, nobody has put the answers in one table.

  • Nobody knows where the wrong claim comes from

    The engine built the answer from a Reddit thread or a stale directory listing, or it is quoting a competitor’s comparison page. Until you know which, you send the correction to the wrong place.

  • It surfaces in the worst room

    A prospect quotes it in a sales call, or a board member reads it out, or a customer brings it up at renewal. By the time you first hear the claim, it has already cost you something.

  • The truth is split across three teams

    Brand owns the story, PR owns the news, and product owns the specs. Each team holds a piece of the truth, and nobody checks any of it against what the engines say.

Why now

The answers are wrong often enough to check, and they change between reads.

45%

of AI assistant answers had at least one significant issue

Sourcing was the most common problem, in 31% of answers, across 3,000 responses checked by journalists in 18 countries. Nobody has checked the ones about your brand.

Source: EBU and BBC, News Integrity in AI Assistants (Oct 2025) (opens in a new tab)

35%

of the time, leading AI tools repeated a false claim in the news

Up from 18% a year earlier. As the tools added web search, their refusal rate fell from 31% to zero: they now answer everything, from whatever the web says. 10 tools, August 2025.

Source: NewsGuard, AI False Claims Monitor (Aug 2025) (opens in a new tab)

<1%

chance that two answers to the same brand question list the same brands

2,961 runs of 12 recommendation prompts on ChatGPT, Claude, and Google AI Overviews, by 600 volunteers. One screenshot is one draw, so an audit has to read a whole window of them.

Source: SparkToro, January 2026 (opens in a new tab)

85%

of B2B buyers think more highly of a vendor when an AI answer includes it

1,076 software buyers, March 2026. 69% chose a different vendor than planned on a chatbot’s say-so. The description is doing the selling, whether or not it is true.

Source: G2, The Answer Economy, 2026 (opens in a new tab)

How the audit works

The platform records, a person reads, and you get a report

Four steps, from the first question to the walkthrough call.

The question set and the run

The questions people ask about you, run daily on every major AI engine

The audit starts with a question set, branded prompts and unbranded ones: what a buyer, a journalist, a candidate, or a partner would ask about you, your products and prices, your people and locations, and your category. Each prompt is set per market (the US, the UK, Brazil, or Greece today) and per persona, so a candidate’s questions and a buyer’s are read apart.

Every prompt then goes to ChatGPT, Gemini, Perplexity, Copilot, and Google AI Mode once a day. The platform keeps each full answer, every source it cited, which brands it named, and how early. Answers vary between runs, which is why the run is daily and the audit reads a window rather than one screenshot.

  • Branded and unbranded prompts, per market and per persona
  • Every answer kept in full, with its citations and the brands it named

The read

A person reads every recorded answer and logs each claim about you

There is no automated accuracy scorer. The platform records, and a person on our team reads. They go through the recorded answers for the window, engine by engine and market by market, and log every claim about you as correct, outdated, wrong, missing, or unfavourable framing.

Each entry carries the engine, the country, the prompt it came from, and the source the answer cited for it. So a wrong price gets logged as “ChatGPT, US, citing a 2024 directory listing” rather than “ChatGPT is wrong”. Missing counts too: the product you launched that no engine has heard of.

  • Five statuses: correct, outdated, wrong, missing, unfavourable framing
  • Every claim tied to an engine, a market, a prompt, and a cited source

The source map

Which sources shape the answers, and who owns them

The cited-domains and cited-pages tables show where the answers come from: your own pages, competitors’ pages, directories, Reddit threads, YouTube reviews, review sites, news, Wikipedia, each marked as yours, a competitor’s, or third party. We trace every wrong claim in the log back to a row in these tables.

That is what turns a diagnosis into a plan. A wrong claim that traces to your own outdated page is a one-day fix. One that traces to a directory or a Reddit thread takes a different route, and one that traces to a competitor’s comparison page means writing a page of your own.

  • Cited domains and pages ranked by how often the engines lean on them
  • Reddit, YouTube, and LinkedIn pages listed separately, with whether they mention you

The report and the choice

What each engine gets right and wrong, and what to fix first

The report says what each engine gets right and wrong, where the wrong claims come from, and how you compare with named competitors on share of voice and position. It ends with a prioritised list of fixes, each with an owner: a page to correct, a listing to claim, a comparison to publish, a source to approach.

You get it as a saved report on the platform, which your team can reopen and share by URL, and as a walkthrough call. Then you choose: Managed GEO, where our team ships the fixes and keeps reading the answers, or GEO Consulting & Trends, where your teams ship them with the tracking running underneath.

  • A saved report, shareable by URL, with deltas against the previous window
  • A fix list with owners, ordered by how many wrong claims each item clears

After the audit

Who fixes what it finds

Both engagements start with this read. What changes is who does the work that follows.

For small and medium businesses

Managed GEO

You get the accuracy audit, then we fix what it found: we correct the pages the engines cite, claim and update the listings, publish the comparisons and answers that are missing, and keep reading the answers every month to confirm each claim has changed. One call a month. From $990 a month, scoped after the audit.

See Managed GEO

For large companies

GEO Consulting & Trends

You get the accuracy audit as a report and a walkthrough, per market, with the fix list handed to the teams that own each source: web, PR, product, people. We keep the daily tracking running so your teams see each claim change as their work lands, plus a monthly briefing on what moved in your category. Quoted per engagement.

See GEO Consulting & Trends

Questions people ask about the audit

Before you ask for one

Is the accuracy audit the same as the free AI visibility audit?

No. The free audit comes first, and every engagement starts with it: it checks whether AI crawlers can read your site and what your pages give them, and takes a first look at where you land in the answers against competitors. The accuracy audit is the second half, and it comes with a scoped engagement. It adds a question set per market, daily runs on every major AI engine, and a person reading the recorded answers claim by claim. It is the first deliverable of both Managed GEO and GEO Consulting & Trends, and we plan the rest of the engagement from its report.

Is the accuracy check automated?

The recording is. The reading is not. The platform runs each prompt once a day on ChatGPT, Gemini, Perplexity, Copilot, and Google AI Mode, and keeps the full answer, every cited source, and which brands it named and how early. It does not judge whether a claim is true, and we have not met a tool that can. A person on our team reads the recorded answers, logs each claim about you with its status, engine, market, and source, and writes the report. That takes longer than a score would, and it is the only version we would put our name on.

Why read a window of answers instead of asking each engine once?

Because one answer is one draw. Ask the same engine the same question twice and you can get a different list of brands, or a different price cited to a different source. A screenshot from one person’s account tells you what that person saw that day. The audit reads every recorded answer for the window, usually the first weeks of tracking, so each claim is logged with how often it appeared and on which days. A wrong claim that turns up in most runs goes to the top of the fix list; one that appeared once gets noted and watched.

What counts as a wrong claim?

A statement about you that is not true today: a wrong price, a wrong owner, a product you discontinued, a location you closed, a person who left, a feature you do not have, or a competitor’s product attributed to you. We log those separately from outdated claims, which were true once, and from missing ones, where the engine does not know something you would want a buyer to hear. Unfavourable framing gets its own status: a claim that is accurate but chosen against you, such as an old complaint quoted as the summary of your support. Every entry names the engine, the market, and the cited source.

Once the report is in, who fixes the wrong claims?

That is the choice the report sets up. On Managed GEO, our team does it: we correct the pages the engines cite, update or claim the listings, publish the comparisons and answers that are missing, and keep reading the answers each month to confirm the claim has changed. On GEO Consulting & Trends, the fix list goes to the teams that own each source, and the daily tracking keeps running so they see each claim move as their work lands. Either way, we will not give you a date by which an engine will say the new thing, but we will show you the day it does.

See what AI is already saying about your brand.

A free audit shows you exactly where you stand across ChatGPT, Gemini, Perplexity, Copilot, Claude, Grok, and AI Overviews, and what it would take to close the gap.

Run a free audit