Privacy-First Discovery: Next Generation PII Detection, Redaction, and Protection Workflows

Privacy obligations are now a central part of every discovery project. Modern datasets contain sensitive information in every corner, from email headers and spreadsheets to chat exports, cloud collaboration tools, mobile collections, and even embedded metadata. With increasing regulatory scrutiny and rising client expectations, legal teams must make privacy protection an integral part of early discovery planning instead of a step that only appears at review or production. 

Addressing Privacy as Part of Overall Strategy 

The variety of modern data sources means that sensitive information no longer appears in predictable fields or formats. Names, account numbers, health details, internal identifiers, and personal notes can appear inside comments, emojis, image text, file properties, or threaded conversations. Teams that rely on manual searches or simple text patterns often overlook key issues or spend significant time correcting incomplete or inconsistent work later in the process. 

Building privacy workflows into the earliest stages of discovery helps reduce downstream risk and supports a more consistent process, particularly when working with large or complicated datasets. 

Automated PII Detection for Modern Data Types 

Advances in recognition technology now allow discovery platforms to identify sensitive information with greater accuracy, even when it appears in unconventional formats. Effective tools can locate PII in multilingual text, nested comments, and unstructured message threads. They also identify PII in nontraditional data types, such as: 

• Chat and collaboration platforms like Slack, Teams, and WhatsApp 

• Images and scanned documents using text recognition 

• Audio and video files using transcript extraction 

• System logs, exports, and other machine-generated files 

These advances help teams quickly surface high-risk content and route it into focused review paths. They also reduce time spent reviewing documents that contain routine or repetitive categories of sensitive material. 

How RelativityOne Supports This Work 

RelativityOne includes several capabilities that fit naturally into privacy-first workflows.   

Main features include: 

• Automated entity detection that identifies names, locations, addresses, email patterns, and other common PII categories 

• Analytics that group similar documents, which helps isolate clusters that are likely to contain repeated sensitive elements 

• OCR and transcript extraction that allow PII identification in images, videos, and other nontraditional formats 

• Customizable rules that can flag specific types of high-risk content early in the workflow 

These capabilities help teams detect sensitive material in both common and emerging data types without relying solely on manual review. 

Smarter Redaction for Consistency and Defensibility 

Redaction has moved far beyond drawing boxes on documents. Modern tools now allow legal teams to apply consistent, rule-driven redactions across large volumes of material. Effective solutions support: 

• Bulk redaction across sets of documents 

• Validation tools that check for missed content before production 

• Redaction of images, PDFs, spreadsheets, and chat transcripts 

• Automated logging that captures the reason for every redaction 

RelativityOne provides a set of redaction tools and workflows that work across multiple file types. It also supports structured workflows that combine review decisions, redaction rules, and audit history into a single defensible process. This level of consistency is especially valuable in matters with tight deadlines or large productions. 

The Path Forward for Privacy-First Discovery 

Tools and processes around privacy in ediscovery is no longer a specialized niche. It is becoming a major part of responsible data handling in litigation and investigations. Automated PII identification, improved redaction workflows, and better handling of modern communication formats allow teams to meet privacy obligations without slowing down review. 

RelativityOne plays a meaningful role in these developments. Its detection, analytics, and redaction capabilities help organizations handle sensitive data with reliability and consistency, even as new data types enter the discovery landscape.  When coupled with an expert provider, these workflows and tools can save countless hours in discovery.