RenewData Introduces Enhancements to its Language-Based Analytics Dashboard

Global News

04
Feb
2014

Editor

RenewData, a legal consulting and technology company with solutions that address the full spectrum of the Electronic Discovery Reference Model (EDRM), today announced enhanced dashboard features for its Language-Based Analytics offerings that help in-house counsel monitor review progress, focus review efforts and prepare for depositions.

The dashboard for Language-Based Analytics, which integrates with kCura’s Relativity, consists of widgets that provide on-demand metrics for:  

• Hot Custodians tracks who has been talking about what and when. It also helps quickly identify relevant people for a particular issue when there are multiple issues and numerous witnesses.
• Review Status by Custodian reports on the review progress for individuals. This is helpful for deposition preparation. It also shows how many documents have had eyes-on review and how many documents have been automatically classified using Language-Based Analytics Review Acceleration.
• Hot Time Frames shows when people were talking about an issue so you can focus your search within the relevant time window. 
• Review Acceleration reports on review progress over time and shares the force multiplier effect of Language-Based Analytics in shortening the review process.

“With the amount of data contained in modern document reviews, it is often difficult for counsel to identify high-priority and relevant aspects of the process as they develop,” said Andy Kraftsow, Chief Scientist of RenewData. “The Language-Based Analytics Dashboard illustrates the value of knowing exactly how people talked about each issue, a benefit unique to Language-Based Analytics users.”

Language-Based Analytics relies on a patented highlight-driven bulk tagger and patent-pending keyword development technology to increase the speed and reduce the costs of today’s document reviews. When paired with the Language-Based Analytics Dashboard, the result is a more efficient and effective document review process that can be completed before 20 percent of the collection has been reviewed.