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  • Dialing up potentially reponsive information from mobile devices
    While mobile device technology may still be novel and nascent, the
    discovery-related legal issues are not. Learn ways to manage the challenge mobile device data presents during the discovery process.
  • Case Studies: Real problems, real solutions
    Read these real-life scenarios to learn about the types of discovery challenges and solutions your peers have experienced.
  • Discovery Insights: Questions about issues that matter
    Stay current on the latest trends with our Discovery Insights series, a Q&A perspective that answers the tough questions on some of the most pressing topics in the industry.
  • Deloitte achieves Orange-level Relativity Best in Service status
    Deloitte’s Discovery practice has achieved kCura’s Orange-level Relativity Best in Service recognition for exceptional customer service for Relativity end users. Read the press release for more information.
  • Bringing eDiscovery In-house: Designing a playbook for your organization
    eDiscovery can be complex, requiring specialized knowledge of legal procedures, information technology, and the flow of information within a company. Learn how companies can improve effectiveness by developing and codifying a set of procedures into a formal document; an eDiscovery playbook.
  • Defensible Deletion: Why data hoarding represents risk and what organizations can do to minimize it
    Learn about strategies, tools and processes you can use to reduce the troves of unnecessary data residing on your servers, in the cloud or on other devices, while retaining the data you need or want.
  • Discovery Insights: 5 questions about mobile device discovery and investigations
    Why is it important to consider mobile devices in eDiscovery investigations? Read this interview to learn more about the potential value of data found only on mobile devices.
  • Discovery Insights: Making the case for managed document review
    Document review can be challenging. Find out how a managed document review approach could help improve speed, quality, and cost-effectiveness of your review.
  • An empirical analysis of the training and feature set size in text categorization for eDiscovery
    In this paper, we examine the factors impacting the training set in a predictive coding model. Find out how we determined that when it comes to the size of training sets, one size does not necessarily fit all.
  • Introducing dynamic review: Document review in new perspective
    Our discovery methodology deploys advanced analytics, including predictive coding, to enhance document review management and reduce costs. You can make more intelligent decisions without necessarily leaving your existing platform or purchasing technology.
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