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Epiq AI’s PII/PHI Review workflow streamlines privacy and data breach review by automating the detection of personally identifiable information (PII) and protected health information (PHI), and by identifying the individuals that information belongs to. Using AI-driven analysis of document text, it helps teams apply a consistent element taxonomy across large datasets and produce defensible, reportable counts of what was exposed and who was affected. The workflow is optimized for incident response, where scope and notification obligations have to be established quickly and evidenced later. This workflow is available as a template optimized for PII/PHI review, allowing you to get started quickly using a proven configuration that includes a standard PII and PHI element taxonomy. You can run individual components independently to execute a specific analysis step in isolation, or deploy the full workflow to run both components in sequence using the current configuration. This flexibility supports a range of review strategies, from a scoping pass over a sample set to a full end-to-end privacy review.

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Key capabilities

  • Automated detection of PII and PHI at the document level, with the specific elements found and the supporting text for each one.
  • A standard element taxonomy covering government identifiers, financial and payment data, credentials, biometrics, and health identifiers and clinical categories — fully editable per matter.
  • Confidence levels and model scores on every determination, with full reasoning transparency.
  • Automated extraction of affected individuals, consolidated across the document population with their contact details and the elements exposed for each of them.
  • Reportable outputs built for incident response, including an affected-individual count, a sensitive data element breakdown, and an exception report that accounts for every document submitted.
  • End-to-end workflow configurability (edit element definitions, adjust scope, run components independently, and tailor the process to each matter).