Everlaw new capabilities better meet legal teams’ cost and early risk assessment needs
Everlaw, the cloud-based ediscovery and litigation platform, announced its Q1 platform updates as part of its monthly release cycle, which includes early case assessment capabilities, production automation features and connector to Microsoft Office 365. These new features provide legal teams with sophisticated technology to improve efficiencies and substantially reduce discovery costs, giving legal professionals the time and resources to dedicate to case strategy and uncovering the data that matters most.
Discoverable data volumes have grown significantly and the pandemic has only accelerated the increase in digital data. In early March 2020, Microsoft Teams hosted 4.1 billion meeting minutes a day, Google Meet recorded 3 billion daily meetings minutes and Zoom’s daily user count surged to upwards of 200 million. Since 2018, Everlaw has automatically transcribed over 100,000 hours from 3.3 million audio and video files, helping legal teams manage and review the surge in audio and video data at no additional cost. Secondarily, the influx has put immense pressure on legal organizations to not only host and organize data remotely and securely, but draw insights for cases in an efficient and cost-effective manner. In fact, data hosting has proven to be such an undertaking that teams typically are unable to efficiently review the data and documents to better inform their cases.
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Legal teams need modern solutions that promote cloud-native application collaboration and Everlaw’s latest platform releases meet this demand. Everlaw’s early case assessment (ECA) functionality delivers an environment to identify and eliminate irrelevant data, pinpoint potentially relevant insights, and determine risks and benefits of taking a case to trial or settling out of court. Users can prioritize review of data and view processed documents in a staging area, not limited to just text and metadata, allowing them to better inform and set case strategy.
Historically, processing and reviewing non-responsive data, or evidence that exists but can’t be used in a case, has been time-consuming and expensive. ECA substantially decreases discovery costs, eliminates third-party processing fees and reduces the data set size upfront which in turn lowers hosting costs. For example, a law firm using Everlaw’s ECA for a large construction matter was able to reduce data volumes by over 70%.
Additionally, Everlaw’s integrated pre-production quality assurance feature identifies 16 common production issues and provides suggested fixes for each, which helps teams initiate productions with more confidence. Now users can stay informed of potential quality assurance warnings and receive recommended fixes that they are able to apply before production deadlines.
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“Everlaw is a pioneer in the ediscovery and litigation industry due to its best-in-class platform that provides legal teams with valuable case-building resources,” said AJ Shankar, CEO of Everlaw. “Product innovation has been a top priority this past year, especially as legal teams faced unprecedented challenges, and demand for cloud-based collaboration tools surged. We’re constantly evolving the product to ensure that cooperation, organization, and development of cases is cost-effective, seamless and streamlined in remote environments.”
Additionally, Everlaw released a Microsoft Office 365 connector to ensure teams are able to better collaborate remotely and make use of newfound data from their various cloud-native applications. The Microsoft Office 365 connector accelerates review cycles by permitting teams to upload Microsoft Office 365 data directly into the Everlaw platform. Everlaw is planning to release additional connectors with other cloud data sources throughout the year that will allow teams to instantly upload application-specific data into Everlaw’s platform. As cloud-native apps and services become more ingrained in their day-to-day work, legal teams can now benefit from integrating with these rich data sets seamlessly.
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