Casepoint launches CaseAssist to cut document review time
Casepoint, a leader in cloud-based legal technology solutions, is enhancing its built-in AI and advanced analytics technology, CaseAssist, with features that give users more insight and control over the analytics process with visualization capabilities and configuration templates.
The predictions generated by Casepoint’s CaseAssist technology in e-discovery, 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.
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.
“At Casepoint, we do not see AI as ‘nice to have’—rather, it’s a core part of our technology,” said Vishal Rajpara, co-founder and chief technology officer at Casepoint. “Increasingly, both law firms and legal departments recognize that using analytics can increase competitiveness, efficiency, and knowledge across a broad range of activities, including case strategy, early case assessment, litigate-or-settle decisions, and much more. We take a human-centered design approach in development with the intention of making advanced e-discovery solutions accessible to users of all technological abilities. It’s all part of our commitment to continuous innovation so we can respond quickly to our customers’ rapidly evolving business requirements and use cases.”
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.
CaseAssist Active Learning supports full verification, precision, recall, and F-measure reporting. With CaseAssist’s multi-classifier classification feature, users can train the system to identify multiple tags within the same training set.
CaseAssist is commonly used in intelligence mining, early data analytics, investigative analytics, review prioritization, and coding validation. CaseAssist also includes chat-guided workflows with natural language interaction and enables users to quickly find key documents by answering simple questions.
For more information about this release, visit www.casepoint.com.