A credit reporting agency builds its risk assessments from a wide variety of publicly available sources — newspapers, court proceedings, regulatory filings, records filings, sanctions lists, and government records. The raw material is inherently messy: it arrives as multi-modal content (text, scanned documents, tables, and images) across many languages, and the same entity is often referred to inconsistently from one source to the next.

Analysts must locate the relevant records for each party, read and interpret them, reconcile conflicting or partial information, and record a standardized summary into an internal database. Done manually, it is a tedious, judgment-heavy process repeated every day across a large team — and one that scales only by adding people.