An AI fact checker that actually catches hallucinations.
A separate checker model reads every drafted article and checks each claim against the sources saved during research. Claims the sources back stay, some get softened, and the rest are cut. An article with a fact problem it could not fix waits for your review.
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What is an AI fact checker?
An AI fact checker is a verifier system that runs on AI-written content, checking every claim against real sources before publish. The honest ones use a separate model from the writer (so the verifier has no incentive to defend the writer's claims) and check against source text, not training-data recall. TheSEOAgent runs this stage on every article it writes: each claim is checked against the pages saved during research, unbacked claims are softened or cut, and an article with a fact problem it could not fix is held for your review. $99 a month, flat.
Generate confident-sounding nonsense, then ship it.
Every popular AI writing tool today asks the writer model to self-check its own claims. The same model that hallucinated a stat is asked whether the stat is real. Predictably, it says yes. The hallucination ships, the article gets cited, the citations propagate. SEO traffic comes; trust does not.
- Writer-model self-check, the worst possible verifier choice
- No source check, claims are vibes-based
- No quoted source behind a claim, so nothing to check it against
- No hold on an article with a known fact error
- Reader catches one hallucination, leaves and never returns
Runs a separate checker model on every claim, against saved sources.
After the writer drafts, a different model reads every claim against the sources research saved for that article. A claim only stays when the quoted evidence is really in a source. The rest get softened or cut, and if a fact problem survives the repair pass, the article is held for your review. The fact-check stage is one of the named stages inside our automated content pipeline.
- Separate checker model, not the writer self-checking
- Every claim checked against saved source text, not training-data recall
- A quoted source behind every claim it keeps
- Articles with an unfixed fact problem held for your review
- Defensible against the next reader who Googles your stat
Four reasons separate verification beats writer self-check.
Different model than the writer, the only setup that catches anything.
A writer model self-checking is theatre. We use a different model with a different prompt operating on the finished draft. That model has no investment in defending the writer's claims, so it actually flags problems instead of rationalising them. Most AI SEO platforms skip this stage entirely, which is why their drafts ship with hallucinations intact. Google does not penalize a page for being AI-written, but invented stats are how a page ends up adding nothing, and our guide to whether Google penalizes AI content shows where it draws that line. Same architecture the full SEO automation pipeline uses across every article it ships, not just the ones a human spot-checks.
Verification against source text, not training-data memory.
Models hallucinate confidently because their training data is a year stale and includes plenty of garbage. The checker reads every claim against the pages research pulled from live search results for that article, and a claim only stays when the quoted evidence is really in one of them. If it cannot be backed, it gets softened or cut. The same approach that grounds every variant on the programmatic SEO side of the product. It is also the check that separates our SEO content writing services from a freelancer who cites whatever the model handed them.
Defensible against the next skeptical reader.
Every claim that stays has a quoted passage in a saved source behind it, and the article links its sources where they help the reader. AI-search systems (ChatGPT, Perplexity, Google AI Overview) reward citations heavily because they need attributable sources to surface answers. Articles without citations lose AEO ranking. Articles with them gain it. Pages you already published can be brought up to the same standard, and our guide to AI content optimization covers adding evidence and checking every AI edit on content that is already live. Same citation discipline the automated content pipeline applies to every article shape we ship, not just opinion pieces.
When a fact problem survives the repair, the article waits for you.
A repair pass softens or cuts the flagged sentences, then the checker reads them again. If a correctness problem is still there, or a check could not run, the article is held for your review instead of publishing, even on a project with auto-publish switched on. Two more checks are free to run on any page yourself: the reading level and keyword density checkers. The same claim check runs on every article the pipeline writes, including programmatic batches. Pricing is $99 a month flat, no per-claim meter, no surcharge for repairs.
Four stages. After every draft. Before every publish.
Standard pipeline draft against keyword brief and SERP context. The writer is allowed to be confident; the next stage will catch what is wrong.
A separate model reads the draft and pulls every assertion that could be true or false: stats, dates, named people, named studies, quotes, relationships.
Each claim is checked against the sources saved during research. A claim passes only if the quoted evidence is really in a source. Unsupported or wrong claims are flagged.
Flagged sentences get softened or cut in a repair pass, then checked again. If a fact problem is still there, the article is held for your review instead of publishing.
The honest one-screen comparison.
| FEATURE | THE AGENT | EVERYONE ELSE |
|---|---|---|
| Verifier architecture | Separate model, post-draft pass | Writer self-check (or none) |
| Verification source | Pages pulled from live search during research | Training-data recall |
| Every claim checked against sources | ||
| Holds articles with an unfixed fact error | ||
| Failure logs | Saved with each article | None or in-prompt only |
| Pricing | $99/mo flat, no per-claim meter | Token surcharge or unavailable |
Q.01What is an AI fact checker?+
An AI fact checker is a verifier system that runs on AI-written content, checking every factual claim against real sources before the article ships. The good ones use a separate model from the writer (so the verifier has no incentive to defend the writer's claims) and check against source text rather than training-data recall. TheSEOAgent runs this check on every article it writes.
Q.02How is this different from asking ChatGPT to check itself?+
Self-check is theatre. The same model that wrote a confident hallucination will rationalise it when asked to verify, because the model is optimising for fluent output not factual accuracy. We use a different model with a different prompt, operating only on the finished draft. The verifier has no investment in the writer's claims, so it actually flags problems.
Q.03Will it catch every hallucination?+
Not every one, and no honest tool can claim that. The checker only keeps a claim when the quoted evidence is really in a saved source, and it softens or cuts the rest. It can still miss a claim that a source itself gets wrong, which is why auto-publish starts off and your first articles wait for your approval.
Q.04What sources does the verifier accept?+
The pages research pulled from live search results for that article, filtered for relevance, plus the facts it read from your own site. A claim about your own business needs one of those facts or a page on your own domain; a third-party page cannot back it.
Q.05How long does the fact-check pass take?+
It runs inside the same run that writes the article, so there is nothing extra to schedule and nothing extra to pay for.
Q.06Can I see what got cut?+
Not claim by claim yet. The check is saved with each article, but no screen in the app shows the list today. You read the finished article with unbacked claims already softened or cut, and while auto-publish is off it waits for your approval before anything goes live.
Q.07How much does this cost on top of the pipeline?+
$99 per month flat. The fact-check stage is one of the four pipeline stages, not a paid add-on. No token surcharge, no per-claim meter, no extra fee for the repair pass.
Q.08How does this compare to the full SEO Automation feature?+
The fact checker is one stage of the full content pipeline. The SEO Automation feature covers the whole loop (research, draft, fact-check, publish) for a daily-cadence single-article motion. This page covers the verifier stage specifically because operators search for it as a separate concept and want to understand it before signing up.
Watch the verifier pass on a real article this week.
Three days for a dollar. Connect your CMS, run a brief, and read the article with unbacked claims already softened or cut before anything publishes. Cancel in one click if it isn't catching enough.
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