The short answer
Buyers get a synthetic document pack that measures extraction, spatial understanding, evidence links, uncertainty, and review effort across formats.
The decision standard is simple: preserve the source, state the limits, and make the next human check obvious. A useful article should reduce uncertainty without pretending that every unknown has been resolved.
What to examine
A tool that handles plain paragraphs may fail on scanned pages, charts, handwriting, multi-column layouts, appendices, or exceptions hidden in footnotes.
Start with scope. Identify the product, account, audience, jurisdiction, data, and decision involved. Then separate what was directly observed from what a vendor, researcher, regulator, or commentator says. Record dates because AI products, access rules, and prices change quickly.
Do not use confidential, medical, legal, financial, or identity documents for the first test. Synthetic fixtures reveal capability without creating a new exposure.
A practical way to do it
- Create a pack with clean text, scans, tables, images, footnotes, and deliberate conflicts.
- Score each extracted claim against the page, region, and source element.
- Require the system to flag unreadable or ambiguous material instead of filling gaps.
Keep the worksheet or test record with the draft. If another editor cannot reproduce the check from the saved evidence, the article is not ready.
Editorial guardrail
Do not fill a missing fact with a plausible sentence. Mark it as unknown, find a stronger source, narrow the claim, or remove it. Commentary belongs in a clearly labeled paragraph after the reported facts, not inside them.
Primary-source reading list
These are starting points, not automatic support for every sentence. The publishing editor must open each cited page and confirm the claim it supports on the day of review.
Bottom line
Buyers get a synthetic document pack that measures extraction, spatial understanding, evidence links, uncertainty, and review effort across formats.