As the e-discovery market matures, new technologies supporting cheaper, quicker and more in-depth analysis have emerged to help companies set themselves apart from the pack. Artificial intelligence processes, process analytics and document review have all found their way into technology-assisted review (TAR) processes, making it sometimes difficult to know what kind of technology a given company is really talking about when they refer to their unique, high-tech strategies.
Andrew Bye, who recently joined Catalyst’s team as director of machine learning and analytics, has been working in the industry long enough to know where machine learning can boost efficiency and where it operates more as a marketing ploy. He discussed his trajectory through the e-discovery market and how he’s seen machine learning grow in TAR processes:
Plugged In
Hometown: I grew up in Newport Beach, California, and have bounced back and forth between southern and northern California since college. I’ve been in San Francisco for about 12 years now and have no intention of leaving.
Why did you join Catalyst?: The people. It was honestly a very easy choice for me. Every single person I talked to from initial phone interviews to in-person meetings in Denver was fantastic. Not only were these people experts in their fields, but I could’ve spent the entire day with any one of them just chatting about our lives and what we’ve been up to recently outside of work. And the more I learned about Catalyst’s amazing technology they’ve developed for Insight Predict, the more appealing the job became.
