kCura has released a short and clear white paper called Understanding the Components of Computer-Assisted Review and the Workflow that Ties Them Together.
It has a short foreword from Katey Wood at ESG which takes as its starting point that investigators “born with ink in their blood” need a new toolbox for navigating digital data.
kCura is able to draw on its own statistics to show the growth in volumes, remarking that the median case size of the hundred largest cases hosting in Relativity grew from 2.2 million documents in 2010 to 7.5 million in 2011.
Whilst this emphasises the larger end of the scale, predictive coding technology has application for much smaller cases than this. The precise workflows and processes may vary with size and type of case, but the broad principles are the same.
Whilst the target audience is obviously Relativity users, most of the principles discussed in the paper are applicable to other applications. This is a straightforward introduction for those who need to understand the principles behind technology-assisted review.
