Use cases
Questions about extracting fields from paragraphs, narratives, and mixed-format documents.
Debt documents
Use an AI extraction workflow that turns debtor details, assets, liabilities, creditor rows, payment amounts, and affordability fields into a normalized table with review flags.
Narrative documents
Yes. Lido can extract structured fields from long narrative proposal documents by using field definitions, custom instructions, review rules, and validation instead of table-only OCR templates.
Unstructured text
Yes. AI extraction can pull defined fields from paragraphs and narrative sections, then structure those values into columns or rows for review and export.
Missing fields
The safest workflow leaves missing fields blank or marks them for review instead of guessing, then uses required-field rules to decide whether the document can move downstream.
Financial statements
Define the insolvency financial statement fields, extract amounts and supporting rows from the document, validate totals, and review exceptions before case-system export.
Changing wording
Use field definitions and examples that describe the business meaning of each value, then validate and review outputs when senders use different phrasing.