LexisNexis says its investment in Knowable underscores the promise and potential of contract data analytics.
LexisNexis Legal & Professional, part of RELX, has entered into an agreement to form a joint venture with Knowable, an enterprise contract intelligence outfit. Knowable was spun off from Axiom Global Inc in February 2019.
Mark Harris and Alec Guettel, Axiom’s co-founders, will lead Knowable as ceo and cfo respectively. Knowable will operate independently, but will benefit from access to the LexisNexis brand, resources, and infrastructure. The partnership aims to further enable LexisNexis to help customers improve decision-making and achieve better outcomes. Knowable supports many of the world’s largest companies, including Dell, GE, and Nestlé USA, providing machine-learning enabled contract data analytics and related contract intelligence solutions. Knowable provides clients visibility into the relationships that govern business activities, mitigates risks, and drives value. By converting legal language into structured data, Knowable helps its clients understand what’s in their contracts, providing a global view of risks, obligations, and entitlements.
With more than 25 million contract data elements analyzed each quarter, Knowable says it combines proprietary machine learning tools with legal subject matter expertise that, together, deliver a full contracts intelligence solution for the enterprise. Knowable will provide LexisNexis customers with leading contract analytics alongside the existing portfolio of advanced technology-enabled decision tools and analytics. LexisNexis Legal & Professional ceo, Mike Walsh, said “This partnership with Mark, Alec and the rest of the Knowable team is in line with our organic growth driven strategy, supported by the addition of targeted data sets and analytics that naturally complement our existing business.” Mr Harris said, “In LexisNexis we've found a partner who believes what we believe about the future of this space and the way in which it will be reshaped by structured data.”