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Documents and AI

Which values are worth extracting

Extracting too much creates review work and returns nothing.

Updated on 13/08/2026

The temptation when configuring a document type is to tick everything that appears on the paper. It is an expensive mistake: every extracted value is one someone will have to review when it comes back low-confidence, and most will never be used.

The question that decides

For each field: **will I filter, alert or decide with this?** If the answer is no, do not extract it. The document is still stored whole and searchable by content; extracting a value is something else.

ValueExtract it?Why
Expiry dateAlwaysIt is what fires the alert
Tax identifierYesIt lets you cross-reference with your system
Insured amountIf you require a minimumIf you never check it, it serves nothing
Insurer nameRarelyYou do not filter on it
Full addressAlmost neverIt is in the document if needed

Important

Extracting personal data you will not use is storing it twice: in the document and as a loose value. If you do not need it to filter or alert, do not extract it — it is the practical application of asking for the minimum.

The sign you overdid it

  • Nobody reviews the low-confidence alerts because there are too many.
  • There are fields nobody has looked at in months.
  • People correct values that change no decision.

Worth knowing

Start with two or three fields per type. Adding one later takes a minute; unlearning the habit of reviewing forty useless fields takes considerably longer.

Can I change the fields on a type already in use?

Yes. What was already extracted is kept.

Can values be extracted without anyone reviewing?

Yes, if the value fires nothing critical. Review is reserved for what decides something.

What if the document does not carry the value?

It stays empty. That is information: it means that document does not serve what you wanted.

A real case

The situation

A company configures fourteen fields per certificate and nobody reviews the alerts any more.

What you do

  1. Keeps three: expiry, tax identifier and insured amount

What you get

Low-confidence alerts drop to a handful and get looked at again.

The situation

Twenty fields are extracted and only three are used.

What you do

  1. Extracts what somebody will actually consult

What you get

Review narrows to the useful.

The situation

A search is made on a field nobody extracted.

What you do

  1. Adds that field to the extraction

What you get

Search finds what is needed.

The situation

Fields already held elsewhere are extracted.

What you do

  1. Checks whether the figure already exists

What you get

Information is not duplicated.

The situation

A warning depends on a date that is not extracted.

What you do

  1. Extracts the validity date

What you get

The warning works.

The situation

Each document type is configured differently.

What you do

  1. Defines what to extract per type

What you get

Documents of the same type are comparable.

This article answers

  • which fields to configure for extraction
  • field map for a document type
  • extracting too many values
  • configure reading per document type