The Inspired Team: Assists in the initial analysis of documents where complex decision making is necessary.
Technology: Algorithims or Language Based Rules are designed to minimize repetitive tasks and apply their rules to reach a statistically valid conclusion on responsiveness and issues and apply to large amounts of data.
Inspired’s suggested TAR methodology centers around Active Learning. Every document call made by a reviewer to an ambiguous document teaches the system how to better identify relevant vs. non-relevant documents. Continuous re-sampling during the document review combined with machine learning increases accuracy to minimize eyes-on review.
Ultimately, our clients are saving around 50-75% of their current Linear Review Costs and Rapidly and Accurately Coding large Volumes of Documents in a much shorter period of time.