eDiscovery Document Review
eDiscovery document review is the process of identifying, organizing, and assessing electronically stored information—such as emails, chats, documents, and files—for litigation, investigations, and regulatory matters. At scale, this traditionally requires large teams of lawyers and reviewers to manually sift through millions of items to determine relevance, privilege, and risk, which is slow, extremely costly, and prone to human error. Modern systems apply advanced automation to prioritize, classify, and filter documents so that humans review a much smaller, higher‑value subset. These tools rank likely‑relevant materials, flag potentially privileged or risky content, and expose patterns or connections across vast datasets, while preserving audit trails and defensibility for courts and regulators. This dramatically reduces review time and spend, helps avoid missed evidence, and enables litigation and investigations teams to respond faster and more confidently under tight deadlines.
The Problem
“Slash review time and costs in eDiscovery with AI-driven document triage”
Organizations face these key challenges:
Skyrocketing costs and billable hours for manual review
Missed or misclassified privileged information and key evidence
Project delays due to review volume bottlenecks