Our summary
A document reader can copy a mistake perfectly, or misread a value that still looks sensible. Unsiloed AI shows how to keep these problems separate. Its fictional six-row medication list has both a stained dose and a clearly printed, unlikely instruction. This is a software demonstration, not evidence of clinical safety.
Unsiloed extracts the text and keeps links to its position on the page. Jev receives the extracted words and context, not the image or reading scores, and judges whether each instruction looks plausible. The application checks both results separately; a strong plausibility answer never cancels an uncertain reading.
People must inspect flagged rows against the original document; neither model guesses a replacement dose. The example cutoffs need testing on documents people have checked, and middling answers deserve caution. Its estimate of about $7.61 for 100,000 similar documents covers Jev alone, excluding extraction and human review.
Key takeaways
- Keep evidence about reading the page separate from judgments about what its words mean.
- Preserve page locations, original values and both review reasons so a person can investigate.
- Treat plausible text as a clue, not proof of a correct reading or a safe prescription.