eBrevia, Leading Enterprise Technology for Automated Contract Review and Analytics, Launches Lease Abstractor

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eBrevia’s Lease Abstractor will leverage the company’s proprietary machine learning technology to bring greater accuracy and efficiency to the lease abstraction process in commercial real estate firms and law firm real estate departments.

eBrevia (http://www.ebrevia.com), the leading enterprise solution for automated contract review and analytics, announces today the launch of the Lease Abstractor, a revolutionary software that accelerates the review and extraction of information from leases.

Founded by Harvard Law School graduates Ned Gannon and Adam Nguyen and computer scientist Jacob Mundt in 2011, eBrevia’s machine learning technology brings greater accuracy and efficiency to contract review and analytics.

Lease abstraction and administration is critical to commercial real estate firms, yet the process has historically proven to be extraordinarily time and labor intensive. This process, whether performed in-house or outsourced, consists of reviewers reading leases and manually extracting data, costing property management organizations fees in excess of hundreds of dollars per lease. eBrevia’s solution was designed to augment the current manual process. The company’s Lease Abstractor product uses machine learning to analyze the lease and extract relevant information based on user specifications. By leveraging eBrevia’s artificial intelligence technology, commercial real estate companies can significantly increase speed and decrease costs associated with lease review and administration.

“In corporate mergers and acquisitions, eBrevia has been able to accelerate the related contract review process known as due diligence by 50%. The company is now excited to bring similar efficiency and accuracy gains to the lease abstraction process for large landlord/tenant firms, property management firms, brokers, REITs, and law firm real estate departments,” said Ned Gannon, CEO of eBrevia. “While other lease abstraction software focuses on the storage and organization of manually extracted data, eBrevia’s artificial intelligence technology actually assists in the extraction of the data itself.”

eBrevia’s technology was incubated in the Computer Science department of Columbia University’s Fu Foundation School of Engineering and Applied Sciences and the company remains a portfolio company of Columbia Technology Ventures, the technology transfer arm of Columbia University. “Real estate lawyers have to wade through massive amounts of text,” said computer scientist Kathleen McKeown, director of Columbia University’s Data Science Institute. “The algorithm we developed can save them time by quickly targeting and summarizing key information in a lease. It’s a good example of innovation made possible by applying data science to the law."

McKeown is on eBrevia’s Board of Advisors, which also includes 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.

For more information about eBrevia, click here. http://www.ebrevia.com

About eBrevia
Based on technology developed at Columbia University, eBrevia provides leading enterprise contract review and analysis solutions, leveraging machine learning to produce faster and more accurate results. 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 in Stamford, CT, eBrevia was founded in 2011 by Harvard Law graduates Ned Gannon and Adam Nguyen and computer scientist Jacob Mundt. The company has raised $2.1 million in seed funding and has offices in Stamford and New York City. eBrevia was one of four national winners in the Startup America DEMO Competition and received the Connecticut Technology Council’s Most Promising Software Product of the Year award.

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