Check AI-assisted claims before they become clean copy.
FactSentinel gives editors a browser-first review trail: the exact claim, source links, model agreement or disagreement, reasoning, caveats, and confidence before a draft or article moves forward.
AI copy can sound polished before it is source-safe.
Editors are often asked to clean up drafts, summaries, newsletters, and marketing copy that may already contain AI-assisted claims. The practical question is not whether the sentence reads well. It is whether a reviewer can inspect the claim before trusting it.
Spot the claim
Select a sentence, statistic, source reference, or draft assertion from the page you are editing or reviewing.
Check the trail
Review the output for source links, reasoning, caveats, confidence, and model disagreement rather than a single opaque answer.
Escalate uncertainty
Use weak evidence, conflicting model reads, or missing context as a signal to request source notes or manual verification.
A review layer for source-aware editing.
FactSentinel is designed for the moment when an editor sees a confident claim and needs a quick first pass before deciding whether to publish, query, or verify manually.
Newsletters
- Stats and trend claims
- Quoted summaries
- Source-heavy blurbs
Draft Review
- AI-assisted paragraphs
- Unfamiliar assertions
- Claims without links
Teaching Editing
- Audit-trail exercises
- Source evaluation demos
- Confidence versus evidence
Keep the uncertainty visible.
A clean sentence can hide a weak evidence trail. FactSentinel keeps the check close to the text so editors can see where the model agrees, where it disagrees, and what sources support the result.
Confidence is useful only when the audit trail survives.
The editor-friendly version of AI fact-checking is not a magic score. It is a visible trail: claim text, model split, caveats, reasoning, and source links a reviewer can challenge.
Common questions
How should editors use FactSentinel?
Use it as a first-pass check for specific claims. Highlight the text, review the source trail and model disagreement, then decide whether the claim is ready, needs a source query, or needs manual verification.
Does this replace human editing or fact-checking?
No. FactSentinel is designed to make uncertainty visible. It helps editors decide where to slow down, not where to stop thinking.
What should I do when models disagree?
Treat disagreement as a review signal. Check the sources, ask for stronger attribution, and avoid turning an uncertain claim into polished copy before the evidence is clear.
Add an audit trail to the editing pass.
Install FactSentinel for Chrome, then check claims without leaving the page you are reviewing.