PLT harnesses the power of machine technology to enhance the effectiveness and efficiency of e-disclosure reviews. TAR uses methods such as predictive coding to assist in review, quality control and document allocation.

TAR is best suited to large-scale cases where the potential review population is very high and timelines are short. Once a subset of data has been expertly coded according to its subject matter, our systems can then be trained to predict responsive and unresponsive documents.

TAR can be used as a quality control method by sampling responsive documents against unresponsive documents to check against human error or by allocating documents for review by using their prediction rank.