New Mexico State Investment Council v. Bland: TAR & Predictive Coding
May 28, 2014•24 min
With 2.6 million pages, thousands of search terms, and hundreds of potential defendants, the counsel in New Mexico State Investment Council v. Bland decided traditional filtering methods would not work. As a result, they turned to Technology Assisted Review (TAR) and Predictive Coding systems to locate relevant data. On this episode of the ESI Report, host Michele Lange interviews Cliff Nichols from Day Pitney and Tony Reichenberger from Kroll Ontrack. Together, they discuss the enhanced abilities and greater efficiencies of TAR and Predictive Coding systems. Tune in to learn more about how these automated systems tap into human expertise to add speed, drive down costs, and increase accuracy during discovery processes. Cliff Nichols is E-Discovery Counsel for Day Pitney, where he directs all electronic investigation. A regular speaker at ediscovery conferences and events, Cliff is recognized as a leader in the cost-saving and efficient use of predictive coding and other types of technology assisted review. Tony Reichenberger is an Advanced Review Services Team Manager at Kroll Ontrack, where he manages document review projects and consults with clients on predictive coding and technology assisted review. Special thanks to our sponsor, Kroll Ontrack.