Leveraging Machine Learning During Document Review: A How-To Guide
Explore machine learning's place in ediscovery
The need for quality tools to help with streamlining review workflows has only become more apparent with the influx of new regulations surrounding data privacy and the existing issues associated with the current state of data management. It will only become more challenging for legal professionals if they don’t develop new strategies and leverage modern technology, such as machine learning, which has emerged as a viable solution to this problem.
Machine learning has had an especially strong impact during review, and as a result, review tools have evolved over the last few years. The most effective solutions feature intuitive user interfaces for discovery, time-saving capabilities like Clustering and Predictive Coding that can reveal the hidden details of documents at scale, and tools that enable automated workflows that enhance and expedite the review process.
In this white paper, we explore machine learning’s place in ediscovery, how Clustering and Predictive Coding work, and four specific steps during review where machine learning can have a tremendous impact.