osint-investigation

Cross-source entity resolution correlates public records across SEC EDGAR, USAspending, OpenCorporates, and other sources to build evidence-backed entity profiles. It normalizes fetched data and generates confidence-scored linkages for due diligence.

An evidence chain in OSINT data integration links disparate public records into traceable, auditable finding JSON. This framework constructs automated evidence chains with confidence-scored linkages to support reproducible offline analysis.

Yes, you can use Python standard library for offline public records analysis. This framework fetches, normalizes, and resolves entities deterministically using only standard library dependencies, ensuring auditable and reproducible workflows.

Temporal correlation analysis on sanctions and contract filings uses a timing module to identify clusters between donations, contracts, or filings. It processes normalized public records to highlight temporal overlaps in entity profiles.

The best way to resolve entities from ICIJ Offshore Leaks and CourtListener is using a deterministic resolution workflow. It links entities across these diverse public-record sources to generate structured finding JSON for investigations.

You need pdfplumber and pypdf dependencies if your public records extraction requires parsing PDF documents. These dependencies support fetching and normalizing unstructured data before cross-source entity resolution and evidence-chain construction.