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Exterro ediscovery platform advances with predictive technologies across the EDRM

Exterro has unveiled the addition of predictive technologies to the Exterro Fusion ediscovery suite. Fusion Predictive Intelligence allows legal teams to apply machine intelligence for the identification and categorization of electronically stored information (ESI) across the EDRM, from pre-collection through review. This latest advancement, now available in Fusion Zeta, was developed in direct response to client and market demand for greater intelligence and cost reduction in the early phases of discovery.

“Multiple ediscovery software vendors offer products featuring “predictive coding” for streamlining costly, manual review. Yet our corporate clients are seeking faster access to the potentially relevant evidence and case facts much earlier in the process, so they can change the course of the matter prior to any evidence being collected,” said Ted Gary, senior product marketing manager at Exterro. “Fusion Predictive Intelligence takes predictive coding to the next level by applying machine intelligence across multiple phases of the ediscovery process.”

Significantly reducing ESI volumes and ediscovery costs
Fusion Predictive Intelligence enables corporations to significantly reduce ESI volumes with advanced machine learning across multiple phases of the Electronic Discovery Reference Model (EDRM), including:

• Early Case Assessment/Identification: Prior to collection, legal teams can now apply predictive algorithms to classify indexed documents and use the results to more accurately and rapidly assess the nature and scope of a matter.
• Collection: Applied at the point of collection, legal teams can now collect and label only those documents identified by the predictive model to minimize data volumes and later stage review costs.
• Review: Post-collection, predictive intelligence can be applied to precisely identify and code relevant documents based on the predictive model, sharply reducing manual review time and costs.

“Predictive coding is one of the assisted review technologies showing significant promise for helping corporations deal with document review, the most expensive part of the discovery process,” said David Horrigan, analyst covering e-discovery and information governance at 451 Research. “We think Exterro is making a good move in adding predictive capabilities to its Fusion platform, especially in making these capabilities part of a workflow that can be applied to earlier stages of the e-discovery process in advance of collection. We expect vendors to continue adding predictive capabilities as corporations continue to grapple with exponential increases in ESI, the challenges of Big Data and rising legal costs.”

“Addressing information governance and data reduction strategies at the outset of litigation and across the entire legal portfolio is extremely important for our clients. The biggest risk lies in entering negotiations without a full picture of the scope, issues and potential risks involved in a matter,” said Bennett Borden, Esq., partner at Williams Mullen. “Exterro’s predictive technologies add another powerful tool that can help our clients not only contain the cost of discovery on one matter but across the entire legal portfolio.”

Fusion Predictive Intelligence is immediately available as part of Fusion Zeta, Exterro’s advanced data management application. More information on the new machine learning capabilities in the Exterro Fusion platform is available here