Advanced Technologies

Epiq advanced technologies save you money, reduce time, mitigate risk, increase consistency, and make understanding data much easier on every project. Imagine that!

Document review is the single biggest expense in most litigation, and review of non-relevant documents is wasteful. Your organization should be able to make decisions on whether to settle or go to trial based on the merits of the case, rather than based on the expense of discovery. Epiq experienced discovery and technology professionals use proven data reduction strategies including filtering, de-duplication, and early case assessment to minimize processing and review costs.

Our advanced technologies save you money, reduce time, mitigate risk, increase consistency, and make understanding data much easier … on every project. Our advanced technology capabilities include:

Artificial Intelligence: From traditional predictive coding workflows to continuous active learning, algorithms can be created to help prioritize review or reduce review populations to significantly decrease cost, increase efficiency, and decrease error.

Categorization: Clusters documents into useful pre-set categories based on seed documents.

Clustering: Automatically identifies conceptually similar documents, empowering early case assessment, first level review, and focusing on what matters in an opposing party production.

Conceptual searching: Goes beyond traditional Boolean searching to find important documents, which is especially useful in factual investigations.

Email threading: Identifies emails that are related and in the conclusions of these conversations so that a reviewer need only review the final email.

Near duplicate identification: Groups like documents together based on textual similarity so you can identify differences easier and make more consistent decisions.

Predictive coding/technology-assisted review (TAR): Epiq predictive coding is a prescriptive linear review workflow—a mix of statistics, categorization, and reporting that can decrease the cost of a review by amplifying the efforts of a small number of reviewers on a large dataset. Predictive coding is particularly useful in regulatory productions when the dataset is enormous and the production deadline is tight.

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