eBrevia Showcases Machine Learning Technology for Commercial Real Estate at RealComm and CRE Tech Intersect Conferences

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eBrevia announces their attendance at the RealComm and CRE Tech Intersect Conferences, where they will exhibit their Lease Abstractor and lead a panel discussion on the transformative role of artificial intelligence in the commercial real estate industry.

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eBrevia, the leading enterprise solution for automated contract review, announced today their participation in two commercial real estate conferences this June, the RealComm Conference from June 9 – 10 in San Antonio, Texas, and the CRE Tech Intersect Conference on June 18 in San Francisco, California.

At the conferences, eBrevia will present their Lease Abstractor, revolutionary software that significantly increases the speed and accuracy of the extraction of key legal and financial data from leases. Additionally, at the RealComm Conference, Co-Founder and COO Adam Nguyen will lead a panel discussion on the new era of data science and lease abstraction, highlighting eBrevia’s work in natural language processing and machine learning technology. The panel discussion: Lease Abstraction - Applying Data Science to Lease Data, will take place on June 9th from 2:45 p.m. to 3:45 p.m. at the Marriott Rivercenter Conference Room 17.

Designed to augment rather than replace manual lease reviewers, eBrevia’s Lease Abstractor extracts a variety of lease information (rent, term, renewal, options, etc.) and can analyze a batch of fifty leases in less than one minute. The software is trained by eBrevia’s experts, who are attorneys and commercial real estate professionals with decades of combined experience from top-tier firms. Unlike a simple keyword search, the software extracts concepts regardless of the vocabulary used to express them.

“We look forward to participating in both the RealComm and CRE Tech Intersect Conferences this June,” Nguyen says. “Our aim is to showcase the pivotal role of artificial intelligence technology in abstracting data for portfolio optimization, property management, compliance, diligence, audits, cost recovery, and budgeting and forecasting. Lease abstraction is critical to commercial real estate firms, yet the process has historically proven to be extraordinarily time- and labor-intensive. Whether performed in-house or outsourced, lease abstraction the “old way” consists of reviewers reading leases and manually extracting data, costing property management organizations fees exceeding a hundred dollars per lease. Our solution was designed to significantly save time and money over the current manual process.”

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 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.

About eBrevia
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.

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Alessia Bell
eBrevia
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