Armed with an understanding of machine learning, ROSS Intelligence is going after LexisNexis and Thomson Reuters for ownership of legal research. The startup, founded in 2015 by Andrew Arruda, Jimoh Ovbiagele and Pargles Dall’Oglio at the University of Toronto, is announcing an $8.7 million Series A today led by iNovia Capital with participation from Comcast Ventures Catalyst Fund, Y Combinator Continuity Fund, Real Ventures, Dentons’ NextLaw Labs and angels.
At its core, ROSS is a platform that helps legal teams sort through case law to find details relevant to new cases. This process takes days and even weeks with standard keyword search so ROSS is augmenting keyword search with machine learning to simultaneously speed up the research process and improve relevancy of items found.
"Bluehill benchmarks Lexis’s tech and they are finding 30% more relevant info with ROSS in less time," Andrew Arruda, co-founder and CEO of ROSS, explained to me in an interview.
ROSS is using a combination of off the shelf and proprietary deep learning algorithms for its AI stack. The startup is using IBM Watson for at least some of its natural language processing capabilities but the team shied away from elaborating.
Building a complete machine learning stack is expensive so it makes sense for startups to lean on off the shelf tech early on so long as decisions are being made that ensure the scaleability of the business. Much of the value wrapped up in ROSS is related to its corpus of training data. The startup is working with 20 law firms to simulate workflow examples and test results with human feedback.
"We really spent time looking at the value ROSS was delivering back to law firms," noted Kai Bond, an investor in ROSS through Comcast Ventures. "What took a week now takes two to four hours."
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The company's initial plan to get to market was to sell software designed for a specific domains of law to large firms like Latham & Watkins and Sidley Austin. Today ROSS offers products in both bankruptcy and intellectual property law. It is looking to expand into other types of law like labor and employment, simultaneously moving down to serve smaller firms.
LexisNexis and Thomson Reuters are frequently on the butt end of claims made by machine learning-powered data analytics startups emerging in a potpourri of industries. A strategy favored by many of these businesses is pushing products to interns and college students for free so that they, in turn, push their advanced tools into the arms of future employers.
"The work ROSS is doing with law schools and law students is interesting," Karam Nijjar, a partner at iNovia Capital and investor in ROSS, asserted. "As these students enter the workforce, you're taking someone using an iPhone and handing them a Blackberry their first day on the job."
Prior to today's Series A, ROSS had secured a $4.3 million seed round also led by iNovia Capital. As ROSS moves to scale it will be navigating a heavy field of mergers and acquisitions and attempts by legacy players to ensure legal tech services remain consolidated.