Product · Docusift

Why every field Docusift extracts carries a confidence score

A tool that reads documents and hands back numbers with no sense of how sure it is has quietly made you the safety net without telling you. Docusift does the opposite: it tells you exactly where it is confident and where it is not.

Reading is a judgement, not a certainty

Pulling a figure off a scanned receipt or a faxed bill of lading is never a certain act. Ink smudges, columns overlap, a decimal point sits ambiguously between two digits. Any honest reader — human or machine — is more sure of some fields than others.

A tool that flattens all of that into a single confident-looking answer is hiding the one thing you most need to know: which numbers to trust and which to look at twice. The uncertainty does not disappear when it goes unreported; it just becomes your problem, found later.

A score on every field

Docusift attaches a confidence score to each field it extracts, not to the document as a whole. The vendor name might come back near-certain while a hand-scrawled total sits low, and you see both, field by field, rather than one blanket verdict over the page.

That granularity is what makes the score useful. A single "this document is 80% good" tells you nothing about which 20% to check. A score per field points straight at the line that needs a human eye and leaves the rest to flow through untouched.

Review as a routing decision

The score is not decoration — it drives what happens next. Low-confidence values route to human review instead of landing unchecked in your ledger, so a person looks at exactly the fields that warrant it and nothing else clogs the queue.

This is what keeps automation honest. The goal was never to remove the human; it was to spend the human's attention where it actually changes the outcome. Docusift is live and accepting sign-ups, and the documents you send stay yours throughout — processed, returned, never resold.

Questions

People also ask

    What does the confidence score apply to?

    Each extracted field individually, not the document as a whole — so you can see that a vendor name is near-certain while a faint total is low, and act on each accordingly.

    What happens to a low-confidence value?

    It routes to human review rather than landing unchecked, so a person looks at exactly the fields that need a second glance while the confident ones flow through.