Stamford, CT (PRWEB) June 16, 2015
eBrevia (http://www.ebrevia.com), the leading enterprise solution for automated contract review, today unveiled eBrevia Bespoke, a product tailoring the company’s proprietary machine learning software to extract custom terms relevant to a particular client’s industry or project.
This latest launch is one more example of how eBrevia is commercializing artificial intelligence technology to apply specifically to contract review and analytics. eBrevia Bespoke enhances the company’s core products used in mergers and acquisitions and commercial real estate, allowing clients to identify and extract specific, unique terms with unprecedented levels of precision. It also offers clients in any domain the ability to apply cutting-edge contract analytics for faster and more accurate contract review and management.
The Bespoke solution offers two options. Clients can leverage eBrevia’s expertise by having the company’s subject matter experts train the software to identify the client’s custom terms. Alternatively, eBrevia can open its proprietary software training system to clients, allowing them to apply their own industry expertise to extract language relevant to custom terms. With either option, eBrevia’s machine learning experts guide the training process to ensure the same accuracy standards as are found in the company’s ready-made products.
This is the second launch for the company in the past year, following the introduction in February 2015 of the Lease Abstractor, a solution that dramatically accelerates the review and extraction of financial and legal data from leases. The Lease Abstractor is currently in use at some of the largest commercial real estate firms in the world.
eBrevia was founded in 2011 by Harvard Law School graduates Ned Gannon and Adam Nguyen and computer scientist Jacob Mundt. The company’s machine learning technology brings rigorous accuracy and increased efficiency to contract review and analytics. eBrevia’s clients report 50-66% savings in the time it takes to complete due diligence, with significant improvements in accuracy over manual review alone.
“Since we launched our software, clients have requested the ability to search a set of terms customized to their specific industries and projects,” said Ned Gannon, CEO of eBrevia. “We wanted to meet this demand by tailoring the core machine learning technology of our product to help expedite the expensive and time-consuming process of data extraction from contracts, leases and other documents. Our Bespoke solution allows clients to work with our subject matter experts, or to leverage their own expertise to extract provisions that are customized to their needs. In doing so, we are offering another way to bring smart technology into the contract analytics and review process.”
eBrevia’s technology was developed in the Computer Science department of Columbia University’s Fu Foundation School of Engineering and Applied Sciences, and eBrevia remains a portfolio company of Columbia Technology Ventures, the university’s technology transfer arm. Computer scientist Kathleen McKeown, director of Columbia’s Data Science Institute, helped design the algorithm that powers eBrevia and serves on the company’s Board of Advisors. Also on the Board of Advisors are Andy Shane, Managing Director at nSource and former head of Strategy and Business Development at Bloomberg Law, and Jeff Munsie, General Counsel at Merrimack Pharmaceuticals, Inc.
Law firms, commercial real estate firms, and corporate legal departments rely on eBrevia’s award-winning software to make their contract reviews more accurate and cost-effective, and to shorten the review process. The software, which extracts and summarizes key legal provisions and other information, can be used in due diligence, contract management, lease abstraction, and document drafting. Based on technology developed at Columbia University, eBrevia was founded in 2011 by Harvard-educated attorneys and a computer scientist. Headquartered in Stamford, Connecticut with an office in New York City, eBrevia was a national winner in the Startup America DEMO Competition and received the Connecticut Technology Council’s Most Promising Software Product of the Year award.
For more information about eBrevia, please visit http://www.ebrevia.com