Using CAL for eDiscovery

Continuous Active Learning, or CAL, is altering the litigation discovery process.  . As Artificial Intelligence (AI) is increasingly being used to analyze documents and predict whether they’re relevant to specified criteria, CAL is the most effective method of training AI for use in eDiscovery. It allows attorneys to assess relevant documents more rapidly, speeding the entire case preparation process. Due to the sheer complexity and volume of modern data sets, using CAL has become a necessity for in-house attorneys and private firms.

Instead of the protracted learning process during manual linear review, CAL models can be trained quickly and iteratively throughout the entire review process. A human reviewer starts the process to provide the model feedback. Then CAL learns continuously, updating its predictions regularly with new coding decisions from human reviewers. The technology helps attorneys honor their fiduciary duty to clients by verifying the thoroughness of the discovery process and providing faster access to insights and evidence. For organizations searching for a way to enhance litigation discovery and document review practices, CAL is the solution.