Automating eDiscovery: A Strategic Framework

The Concise Framework for Discovery Automation takes the overall process of discovery, breaks it down into a data discovery component and a legal discovery component, aligns these components with insight and intelligence, and then highlights four key processes and eight key tasks that appear to be important in the discovery process across the lifecycle of information and litigation.


A Winter of Discontent? The Winter 2019 eDiscovery Business Confidence Survey

As your opinion is important in helping form a complete picture of the business confidence of those operating in and around the eDiscovery ecosystem, please do take the time to complete this short, anonymized survey, as the results help all legal, business, and technology professionals in the eDiscovery ecosystem better understand the current state of business confidence and how their business is positioned regarding key operational metrics.

Predictive Coding Technologies and Protocols: Overview and Survey

With the growing awareness and use of predictive coding in the legal arena today, it appears that it is increasingly more important for electronic discovery professionals to have a general understanding of the technologies that may be implemented in electronic discovery platforms to facilitate predictive coding of electronically stored information.

SuperCALifragilisticexpialidocious: An Update on One Technology-Assisted Review Protocol’s Terminology

With recent eDiscovery┬áprovider announcements that highlight the use of the terms “Continuous Active Learning” and “CAL”, provided below is a quick review and current update on Recommind’s (Recommind, Inc.) opposition to the trademark/service mark application by Maura Grossman and Gordan V. Cormack for trademarking CONTINUOUS ACTIVE LEARNING and CAL.