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Time is running out and the new year will be here before you know it—what are you going to do for a review platform next year?!
Paragon Legal Technology Support, a managed services provider to specialized litigation groups based out of Atlanta, Georgia (www.paragonafa.com), recently concluded a multi-year review project utilizing iCONECT’s XERA® document review platform, in combination with XERA Analytics (powered by CAAT® from Content Analyst Company). This project provided a unique opportunity to quantify the difference in results between a “linear” review versus an “analytics review.” Rarely does one litigation matter provide the unique scenario to have the same review teams reviewing the same datasets using different methods within a compressed time period. Such were the circumstances during Paragon’s recent document review of 7TB of data.
2016 budgeting season is here and many firms find themselves disenfranchised from their document review platform of choice, or worse, forced to lock themselves into a long-term commitment for an expensive, unwanted bundle, that doesn’t even qualify as best-in-class.
Download “Reinventing the RFP” document and read about the top considerations for your next document review platform RFP.
LogicForce Consulting has adopted the best-of-breed approach to eDiscovery, but they found that using a variety of different tools led to inefficient processes. Learn how LogicForce reduced cycle time by more than 60% using the Direct to Database (D2D) integration between Nuix eDiscovery Workstation and iCONECT-XERA.
Even though predictive review has been proven to be more accurate, reduce cost and create a balance between cost and benefit, it is difficult to justify an alternative to the traditional review process… In Part 2 of this series, we discuss the three other major justifications for not adopting predictive review.
We are swimming in data. According to IBM, we create 2.5 quintillion bytes of data every day, and that number is growing faster than ever. Ninety percent of the data in the world has been created in the past two years and “The Internet of Things” will create even more without human intervention. All this data—combined with tight timelines for litigation and regulatory investigations—can make document review projects impossible through traditional means and in some cases technological assistance becomes a must to meet the deadline.
In Part 1 of this series, we discuss the first of four major justifications for not adopting predictive review.
In many instances, the “completion” (pretrial presentation) of an eDiscovery project is the “production” of documents that will meet the requests made by the other side. The challenge in meeting production requests and specifications can be the variety of document types – from generic (Microsoft) Word and Excel documents to (Adobe) PDF. Some collections may also include CAD drawings, videos, or obscure file formats that are proprietary to an industry. Documents may contain privileged information, trade secrets, Personal Health Information, or Personally Identifiable Information (PII), which require redaction for appropriate protections.
Since productions themselves are meant to contain the relevant documents, a well-thought-out production process is key to both meeting the needs of the production request and the needs of the client. Through many years of experience in creating productions, we’ve been able to identify a number of issues that may arise, and offer suggestions on how to resolve them.
Short for Health Insurance Portability and Accountability Act, HIPAA provides standards to protect the privacy of personal health information. To improve the efficiency and effectiveness of the health care system, the Health Insurance Portability and Accountability Act (HIPAA) of 1996, Public Law 104-191, included “Administrative Simplification” provisions that required HHS to adopt national standards for electronic health care transactions. Congress incorporated into HIPAA provisions that mandated the adoption of Federal privacy protections for individually identifiable health information.