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Glossary

What is documentdata extraction?

Document data extraction pulls defined fields (names, dates, amounts, line items) out of documents and delivers them as structured data: JSON, database rows, API payloads.

Definition

From document to fields.

Document data extraction is the step that turns a document into usable values: the invoice number, the gross total, the transaction table, the contract parties. Input is a PDF, scan, email or photo; output is structured data in a defined shape.

The hard parts are not the obvious fields but the edge cases: multi-page tables, values that appear under different names, figures whose meaning depends on a footnote. Extraction quality is decided there, and by what happens when the system is unsure.

Any source

PDFs, scans, emails, photos, in mixed quality and any language.

Fields and tables

Header fields, repeated line items and complex tables, extracted into one defined structure.

Structured delivery

Results leave as JSON, database rows or API calls, ready for the receiving system.

In practice

Extraction in MiruIQ.

MiruIQ extracts against schemas you define, with no pre-trained document types: any document you can describe is extractable, complex tables included, and every extraction can be validated and human-reviewed before delivery.

FAQ

Document data extraction questions

What teams evaluating extraction ask most.

Which document types can be extracted?

With schema-driven extraction: any type you can describe. Invoices, bank statements, payslips and delivery notes are common, but the mechanism is generic, so registry extracts, lab reports or industry-specific forms work the same way. There is no fixed catalog of supported types to be limited by.

What determines extraction accuracy in practice?

Less the raw model and more the system around it: validation that recalculates figures which must add up, cross-document checks, confidence thresholds, and a review queue for the uncertain rest. A system that knows when it is unsure and asks a human beats one that is confidently wrong.

Start now

See it on your own documents.

The 14-day free trial covers 200 documents: enough to define your schemas, run real files and measure the results before anyone calls you.