Insight Predict is a second-generation TAR engine designed to help reduce review costs and time for outbound productions, deposition prep and early case assessment.
In July 2014, two of the leading experts in e-discovery, attorney Maura Grossman and professor Gordon Cormack, published research on the effectiveness of a new learning protocol for Technology Assisted Review called “Continuous Active Learning," or CAL for short. As shown in their research, CAL finds relevant documents faster and at lower cost than traditional TAR engines, speeding up review and cutting costs. It also simplifies the review process, solving the real-world problems that held back TAR from the beginning and making it effective in a much broader range of cases.
Insight Predict is built on a powerful Document Relationship Engine. Start with key documents and quickly find others that matter most, while discarding those that don’t.
Despite best efforts from your review team, privileged documents may still slip through the cracks. TAR can help find them before they get loose.