Casepoint has announced that its built-in AI and advanced analytics technology, called CaseAssist, has been upgraded to give users more insight and control over the analytics process with enhanced visualization capabilities and configuration templates.

The predictions generated by Casepoint’s CaseAssist technology in eDiscovery, investigations, and other document-intensive review projects eliminate the need for users to review documents that are nearly certain to be non-relevant, saving thousands of dollars in review time. Through CaseAssist Active Learning (CAL), users can choose to train a single or multiple models with no sample set requirement and CaseAssist will ensure relevant documents are prioritized for review.

Also, Casepoint’s Dynamic Batch Review workflow seamlessly integrates with CaseAssist to make the transition from prioritization to linear review with ease. Casepoint’s patented AI technology provides users with faster predictions of relevance with extremely high levels of accuracy and quickly identifies connections between people, documents, dates, and terms.

Casepoint’s advanced analytics provide powerful data visualizations, communication analysis, graphing, concept searching, topic clustering, email threading, and near similarity/near dupe detection.

In addition to guiding the user through the oftentimes complex workflow of advanced analytics, Casepoint’s CaseAssist Active Learning utilizes active learning based on the user’s input to continuously predict and rank unreviewed documents.

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