Pre/Dicta Expands its AI-Powered Litigation Prediction Platform: Now Includes Motion for Summary Judgment, Class Certification, Case Timelines, and More

The added features, utilizing cutting-edge AI technology, provide legal teams and their clients with data-centric judicial intelligence to leverage for their strategic advantage


NEW YORK, Nov. 14, 2023 (GLOBE NEWSWIRE) -- Pre/Dicta, the sole AI legal prediction platform, today launched new capabilities, enabling legal teams to predict case outcomes across multiple types of motions and objectively quantify case timelines. Collecting, enriching, and analyzing more than 35 million docket entries, over 3.5 million cases, and 5.5 million parties and firms, Pre/Dicta generates a unique fingerprint or 'DNA' for each case and predicts judicial decisions. The availability of data-centric forecasts for the entire litigation timeline, from filing to trial, equips attorneys and their clients with a strategic edge and facilitates a more highly informed litigation strategy.

Requiring only a case number or caption, Pre/Dicta’s proprietary algorithms, incorporating judicial biographical information and outcomes independent of case facts and legal precedents, use artificial intelligence to uncover judicial patterns to produce reliable predictions. Its predictions are 85% accurate for motions to dismiss across all 94 U.S. federal district courts. The newly released augmented capabilities provide critical insights into additional motions through AI data-profiling. These include the most consequential motions: summary judgment, class certification, and venue transfer. The platform contextualizes its motion analysis, comparing that with the judge's decisions, as well as other judges within the same circuit and those with analogous biographical profiles.

Relying on manually researched historical statistics and anecdotal experiences to predict litigation outcomes is obsolete. Pre/Dicta founder and former litigator Dan Rabinowitz explained that “in the modern legal landscape, understanding the myriad of factors that influence judicial decision-making, and enabling AI to surface critical insights from billions of patterns, is a crucial advantage in any case."

Pre/Dicta's case-specific metrics and outcome predictions now include:

  • Enhanced AI for Outcome Likelihoods of Multiple Motion Types: In addition to motions to dismiss, Pre/Dicta’s powerful algorithm now includes motions for summary judgment, venue transfer, class certification, and motions to compel.

  • Litigation Timeline Predictions: Pre/Dicta provides legal teams with the predicted case-relevant timelines from filing to trial to plan litigation strategies better, allocate resources, and inform settlement decisions.

  • Venue Comparisons: Compare likely outcomes across all Federal venues, giving high certainty to strategic choices regarding venue selection.

In an era where data is the bedrock of strategic decisions, legal professionals and clients are no longer limited to traditional legal analysis. Now, armed with Pre/Dicta's cutting-edge insights, they can anticipate the future and gain an unprecedented advantage—those without this foresight risk being anchored to the past.

For a deeper insight into Pre/Dicta's transformative offerings and to schedule a demonstration, please visit www.pre-dicta.com.

About Pre/Dicta
Pre/Dicta revolutionizes how legal professionals and clients predict federal case outcomes. Pre/Dicta provides insights into judicial behavior beyond human perception through advanced data science and AI. Drawing from extensive biographical data on judges and two decades of docket data, Pre/Dicta stands unparalleled in its predictions, with an impressive 85% accuracy rate. Explore more at www.pre-dicta.com.

Media Contact
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A video accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/c3ab9271-37d9-44b6-99a0-3c018601ed21

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/2197c4cf-1036-4409-87c9-a480f44b9b5d


Pre:Dicta demo screenshot 2