# AI Detector for Editors & Publishers

Batch-check freelance submissions, blog posts and whole URLs for AI writing — with per-line evidence you can send back to the writer. Free to use.

- Source: https://scanforai.com/for-editors
- ScanForAI — AI-writing detection. A score is a signal, not a verdict.

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# Know what you’re publishing.

Freelance copy, guest posts, agency deliveries — paste text, drop a folder of files, or check the live URL. You get a score, the marked lines, and a report you can attach to the conversation with the writer.

## From single drafts to a whole content batch.

### Batch scan

Drop up to 20 files, pasted pieces or URLs and get a scored table — average, outliers, and a CSV export for the record.

### Check live pages

Paste a URL and scan what's actually published — yours or a writer's portfolio.

### Evidence, not accusations

Every score comes with the lines marked and the patterns named in plain English — feedback a writer can act on instead of dispute.

### PDF reports & history

Export a report per piece, keep history per writer, and compare drafts across revisions.

## Common questions.

Yes. Anonymous scans are never stored. With a free account you choose per scan whether to save it to your history.

Send them the marked-up result or PDF report — it shows which lines read machine-written and why. That turns a standoff into an edit list. And remember: no detector is proof; treat high scores as a conversation starter.

The batch tool takes up to 20 URLs at once today; scheduled full-site monitoring is on the roadmap.

Two signals beat any single score: a style break from their past work, and what the scanner marks. Paste the piece — if whole sections light up with stock phrasing and metronome rhythm, send those lines back as an edit request and watch how they respond.

Google's stated target is mass-produced low-value content, however it's made — and in practice thin AI text underperforms. The risk isn't a secret AI penalty; it's publishing writing nobody chose to write. Scan before you publish and fix what reads machine-made.

No — auto-rejecting on a score repeats the false-accusation mistake in commercial form. Use the marked lines as the conversation: heavy marks on a first draft is feedback; heavy marks on a 'final, fully human' delivery is a different discussion.