Our white papers can help you understand Relativity and the e-discovery process at a deeper level, including analyzing the effectiveness of certain methodologies.
Written by the Information Governance Initiative, this paper underscores the benefits of sorting and addressing the data your organization is currently storing-a logical beginning to any IG process.
Dr. Gideon Frieder of George Washington University discusses how statistics—including basic concepts like probability, confidence intervals, and sampling—help make computer-assisted review defensible.
In this paper, we investigate different ways to conduct—and measure the accuracy of—a computer-assisted review project using a control set workflow.
This paper explains the engine behind Relativity Analytics, which uncovers document relationships based on concepts instead of just keywords.
Dr. David Grossman explores how sample size and sampling methodology—including judgmental sampling based on keyword searches—affect the accuracy of a computer-assisted review project.
Dr. David Grossman investigates and explains reporting in Assisted Review, as well as the effectiveness and accuracy of the workflow.
This paper explains the multiple layers of Binders and iPad® security that keep your case documents safe inside the app.
This paper discusses how Assisted Review’s combination of experts, engine, and statistical validation produce defensible results with significant savings in review time and costs.
“As for kCura’s overall Assisted Review workflow, we found that it improved effectiveness with almost each new round that was tried in our testing.”
Dr. David Grossman, Ph.D.
from “Measuring and Validating the Effectiveness of Relativity Assisted Review”