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Casepoint, a leader in cloud-based legal technology solutions, today announced that its built-in AI and advanced analytics technology, called CaseAssist, has been significantly upgraded to give users more insight and control over the analytics process with enhanced visualization capabilities and configuration templates.
The enhancements to CaseAssist come at a pivotal moment for analytics in the legal profession. A recent LexisNexis study finds that 70% of law firms are now using analytics for both and the practice of law and the business of law, 98% indicate legal analytics have improved their firm’s performance, and 92% plan to increase their use of analytics over the next 12 months.
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. Whether your use case involves seeding an algorithm with known relevant exemplars or starting from a complete blank slate, CaseAssist will quickly separate the wheat from the chaff.
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 accelerates time to insight by up to 83%. As an example, a plaintiffs firm used advanced analytics to cull data down for a case involving a group of commercial airlines.
“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 eDiscovery 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.
CaseAssist constantly learns from the decisions and behavior of its users, translating that information into actionable insights and recommendations. Casepoint’s patented AI technology helps litigators improve how they perform mission-critical tasks such as:
“CaseAssist has achieved widespread adoption at our firm, and there are good reasons for that: It’s fast, it’s easy, and the attorneys know it’s there, so they don’t hesitate to ask for it or use it themselves,” said Dana Wesley Sarti, Litigation Support Manager at Robbins Russell. “While DIY timeline analysis and DIY sender/recipient analysis are probably the most popular features for our teams, we also use Casepoint analytics to do things like spot gaps by date or file type in loaded content, determine data volumes by individual custodian, identify odd file types, and identify sender and recipient domains to bulk-identify documents that are unlikely to be relevant for first or early review. Because CaseAssist’s is so simple to learn, more of our attorneys are using it on their own. Also, the use cases are virtually unlimited, which is why adoption continues to increase across the firm.”
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