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Andrea Beckman is a director of product management at Relativity, where she guides development of the platform's review, artificial intelligence, and analytics features. She has more than 15 years of experience in software development and management.
Over the past few years, we’ve reinvented Relativity’s user interface to give case teams more intuitive and visual ways to search and analyze their data. Putting a stop to these email threading pitfalls has always been a big initiative in this revamp.
If you follow any industry publications, you’ve probably heard a lot about the promise of analytics technology in e-discovery. You may be wondering: How many people are really taking advantage of this technology, and will it really save me time and money?
Jeff Gilles joined the kCura team this month with more than 15 years of experience in software, eight of which have been in advanced text analytics and the underlying technology that supports a wide range of features in Relativity Analytics, and he’s ridden the tides of change in e-discovery along the way. We sat down with him to get his perspective on this evolution.
You’ve heard the buzz about text analytics, and you know the technology can help your team realize big savings on e-discovery time and costs. Still, you’re feeling like the sole champion of analytics in your office. Maybe it’s not on your team’s radar yet, or they’re squeamish about straying from linear review—or they’re just not sure where to begin.
Earlier this month, we posted a two-part series on our exciting—albeit rocky at first—journey with analytics in e-discovery, as well as some takeaways from Judge Peck’s recent Rio Tinto opinion. As we’ve mentioned around this topic, there’s been a lot of growth in analytics usage over the last couple of years.
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