Privacy Engineering for Documents and Unstructured Data

Detection of sensitive content in unstructured text, such as contracts, invoices, call center transcripts, medical reports, and legal correspondence, followed by the appropriate privacy-enhancing transformation: suppression, pseudonymization, generalization, or synthetic replacement. The technique is chosen per entity type based on sensitivity, downstream use, and the architecture the data flows through. Pipelines cover both standard identifiers and domain-specific sensitive terms defined by the client.

Deliverables:

• Analysis of document types, data flows, and sensitivity requirements

• Detection and transformation pipeline tailored to the client's document landscape

• Validation report covering detection accuracy, false positive rate, and residual risk

• Integration into existing document processing or LLM workflows