When it comes to electronic discovery (eDiscovery), how evidence is collected can be just as important as what evidence is collected. Emails, text messages, computers, mobile devices, cloud storage, and business communication platforms all contain potentially relevant electronically stored information (ESI). However, not all electronic evidence can or should be collected using the same method.

Learn how law firms can reduce document review costs using deduplication, email threading, forensic tools, and TAR while preserving accuracy.

RelativityOne (often called RelOne) and Everlaw are cloud-based eDiscovery platforms used to manage electronic evidence in litigation and investigations. Both support review, analytics, collaboration, and production. Their differences are better understood as workflow and implementation considerations, not a universal judgment that one is superior. This article compares published capabilities, identifies practical trade-offs, and suggests questions to ask during a demonstration.

Predictive coding is a technology-assisted review (TAR) method that learns from human reviewers’ document decisions and uses those examples to rank or classify other electronic documents. Rather than reading every document in arbitrary order, a review team can focus first on documents the model predicts are more likely to matter. It is a workflow combining legal judgment, software, and quality control; not a substitute for the legal team.

eDiscovery, short for electronic discovery, is the process of identifying, preserving, collecting, processing, reviewing, analyzing, and producing electronically stored information that may be relevant to a lawsuit, investigation, subpoena, regulatory matter, or other legal proceeding. The information involved is commonly called ESI, or electronically stored information.