See the picture ChatGPT, Perplexity and Google have of your brand — the category, the competitors, the reputation — then check every factual claim they make against your own verified content, and fix the pages feeding them the wrong answer.
Assistants synthesise an answer from thousands of sources, then volunteer detail nobody asked for. That is where wrong pricing, retired features and invented policies reach your buyers — and you usually find out from a customer, not a dashboard.
A buyer asks what you cost. The assistant answers with the plan structure from a review round-up written eighteen months ago, and quotes it as fact.
An integration you sunset is still listed as available. One you launched this year is not mentioned at all, because nothing quotable says so.
Return windows, warranty terms, and SLAs get synthesised from whatever the model saw across your category, then attributed to you specifically.
Not one sentiment number. Five dimensions, each scored 0-100 from the specific claims AI engines actually made about you — so a category stays empty until there is real evidence behind it, rather than filling in a comfortable default.
Is your brand described as dependable, safe, and credible?
How AI rates what you actually deliver.
Pricing, ease of use, and support perception.
Whether AI treats you as a recognised, recommended option.
How modern and differentiated you seem.
Pick what you want to be known for. Anything AI does not yet evidence becomes a finding with a fix attached.
Every factual claim AI makes about you, checked line by line against your own verified content — with the correction, the evidence, and the page that caused it.
Every factual assertion AI made about you — pricing, specs, features, availability, policies — pulled out verbatim from your tracked answers. Opinions are left to the perception scorecard.
Not a second model guessing. Your own knowledge base: crawled pages, uploaded documents, and the brand-approved records you signed off in Knowledge Studio.
The citations sitting closest to the claim, each labelled as your site, a competitor, or a third party — because that determines what the fix actually is.
Every run adds a point to your accuracy trend. Fix the sources, run it again, and watch the line move. That is the proof the work landed.
A fact check is only as good as what it checks against. Reaudit's source of truth is not a folder you uploaded once and forgot. Knowledge Studio gives every record a draft-to-approved review workflow, version history, and drift detection that flags you when the underlying source changes — so the thing your accuracy score rests on stays correct as your business moves.
Reviewed and approved by a human before it counts as truth
Versioned, so you can see what changed and when
Drift-monitored, so stale records get flagged, not quietly trusted
If your content does not cover a claim, we say so — it is marked could not verify and excluded from your score entirely. Silence is never scored as a lie. Coverage sits beside the accuracy number so you always know how much was genuinely checked, and every wrong claim shows the source excerpt that settled it.
Knowing AI is wrong is not useful on its own. Knowing which URL taught it, and who controls that URL, is the difference between a report and a task.
AI quoted your site correctly — the page is out of date. Update the numbers, remove the superseded ones, mirror the facts in schema.
Their page is the most quotable answer to your question, so AI uses their framing of you. Publish a better one.
An independent publisher is carrying stale facts. Open an outreach draft prefilled with the claim, the correction, and your source.
Compare your five perception scores against any rival AI names beside you, and see exactly which dimension you trail on. When AI keeps pairing you with the wrong brands, that gap tells you which comparison content is missing.
Your AI presence tracked against branded search and direct traffic, so you can tell whether visibility is turning into demand — and get one recommended play: invest upstream, fix the narrative, build proof, or keep going.
Publish the correction, link it, and Reaudit watches whether AI answers start reflecting it — reported as an outcome per fix, not a vague promise that things improved.
Each finding is paired with the specific work that closes it, ordered by severity, with a copy-ready prompt for your assistant or IDE.
Link the page you published and the phrases it makes. We check whether tracked answers start echoing them.
Each fact check adds a point. Improvement is something you can show, not something you assert.
How the perception scorecard and fact check actually work
Sentiment measures how AI feels about you — positive, neutral, negative. Fact Check measures whether what it says is true. A glowing recommendation that quotes the wrong price is great sentiment and a real commercial problem. They are separate pillars because they need separate fixes.