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Casepoint, a leader in cloud-based legal hold and eDiscovery technology, today announced the release of a major new feature allowing users to leverage artificial intelligence and past work product across multiple matters.
Casepoint will be showcasing the portable predictive AI models feature, along with other advanced analytics features of Casepoint’s legal discovery platform, at Booth #109 during the 2022 CLOC Global Institute (CGI) event in Las Vegas to be held May 9–12, 2022.
Portable predictive AI models allow legal teams to import predictive models from one workspace to another, leveraging existing work product such as AI tags to look for common themes or patterns across similar matters and data sets without having to build a new model from scratch for each new matter. Building on existing models helps legal teams identify important or sensitive information even faster, saving government agencies and corporations, as well as the law firms that represent them, significant time and money, and revealing key evidence earlier in the process of litigation or investigations. In addition, as models learn from more and more matters, they will not only increase review efficiency but accuracy as well.
Casepoint continues to deliver new user-friendly features into its end-to-end legal discovery platform. With AI capabilities like CaseAssist Active Learning and Data Stories, which make up CaseAssist, even non-technical users can apply advanced analytics to data sets and quickly develop a coherent legal argument from a subset of key facts, dates, individuals, keywords, and more. Legal teams use CaseAssist to identify patterns and anomalies and build visualizations from both structured and unstructured data. The teams then glean insights from those data visualizations which help them better understand the evidence and frame legal strategy sooner and quicker.
Continuously learning from user input and the introduction of new data, CaseAssist Active Learning builds prediction models to forecast and rank the relevance of unreviewed documents and quickly find potentially privileged documents. CaseAssist’s predictions identify “smoking gun” documents earlier in the discovery process, eliminating the need to manually review vast numbers of irrelevant documents, and saving thousands—sometimes millions—of dollars in document review while producing more accurate results. Portable predictive AI models further reduce the time required to achieve strategic insight and are built into CaseAssist at no added cost to customers, delivering significant value from deployment onward.
“CaseAssist is breakthrough AI software that dramatically reduces the time and cost of document review, and our new portable prediction model feature turbocharges this process,” said Vishal Rajpara, Chief Technology Officer at Casepoint. “Our customers can intelligently augment searches with machine learning and identify the most relevant documents in a matter more quickly. Legal teams use CaseAssist to analyze and classify documents to accelerate review, build ‘stories’ from the data to inform case strategy and produce better outcomes in less time at lower cost.”
The introduction of portable prediction models comes on the heels of recent Casepoint news about enhanced integrated and automated collection capabilities for Slack, Teams, and other popular collaboration tools that speed the entire eDiscovery process, from legal hold to review and production. Casepoint recently became an official Slack Technology Partner, enabling direct collections from Slack for customers utilizing Casepoint’s powerful eDiscovery and Legal Hold applications. With Casepoint, customers can manage and monitor the entire discovery process—from legal hold to production to review—entirely within its unified platform, eliminating the need to log in and out of other applications or manually transfer files.
Casepoint representatives will be available during CLOC Global Institute at Booth #109.
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