NEW YORK and BOSTON–(BUSINESS WIRE)–Columbia
Business School data scientist Professor Daniel
Guetta, Director of the Business Analytics Initiative at Columbia
Business School and Columbia Engineering, has published a case study
an Artificial Intelligence (AI)-enhanced document management and data
analytics solution for contracts developed by Harvard Law and MIT
researchers. Guetta begins teaching the Evisort case study today in a
new Business Analytics MBA class, the latest in Columbia’s growing data-
and analytics-focused offerings for MBAs. The case study, entitled: “Evisort:
An A.I.-Powered Start-up Uses Text Mining to Become Google for Contracts,”
will be joined by a technical case study counterpart in the near future.
Guetta describes Evisort as a compelling, versatile solution for
AI-driven contract data mining, with strong core utility for lawyers. He
notes that, in addition to their significant usefulness for attorneys,
contract analytics also have vast mainstream potential to assist a wide
range of corporate professionals in finance and operations. Guetta also
acknowledged that artificial intelligence techniques such as those used
by Evisort could also be used to harvest data from many types of
business documents in addition to contracts.
“Contracts are the scaffolding of the modern company,” says Guetta.
“Every department and process within an organization is ruled by
contracts including legal, employment, supply chain, pricing, inventory,
and more. Extracting data from contracts is not only of paramount
importance to lawyers in an organization, but it also has a much more
enterprise-wide, holistic reach with infinite applications.”
Guetta continues, “Extending far beyond legal tech and contracts,
contract-focused business intelligence solutions can form the basis of
hundred-million-dollar savings for corporations because contracts
contain so much essential corporate data. Text mining drastically
reduces the need for manual data searching, reporting and human reading
of contracts except in the most complex cases. Evisort is particularly
impressive because it demonstrates both the power and limits of AI. Even
when human review is necessary, Evisort provides a suite of
non-AI-enhanced tools to go the last mile if needed and reduce review
Evisort CEO Jerry Ting and COO Jake Sussman were Harvard Law School
students when they co-founded the company in 2016 with CTO Amine Anoun,
then a graduate MIT student. All three men have since graduated and are
now full-time executives at Evisort. Evisort is backed by leading
venture capitalists including Amity Ventures and Village Global which
has investors like Jeff Bezos, Mark Zuckerberg, and Bill Gates.
Ting explains, “You can break down a company into its entire value chain
by looking at its contracts…a business intelligence platform centered
around contracts can become a business intelligence platform for the
whole company, from operations, to supply chain, to advertising. Evisort
has unlimited potential for corporations and law firms to mine any type
Guetta’s Business Analytics class at Columbia Business School introduces
MBAs to advanced topics in artificial intelligence. This class is the
latest in a series of data- and analytics-focused classes at the
business school, including classes on databases, Python, R, and applied
data science. The Columbia Evisort case study is now available on the
Columbia Caseworks website here.
is a startup founded in 2016 by Harvard Law and MIT researchers to
develop artificial intelligence (AI) algorithms to help companies mine
contracts for data. Evisort’s AI understands meaning and context in
legal language, virtually eliminating the need to read contracts.
Artificial intelligence specifically designed for contracts is a nascent
and booming industry that Evisort has pioneered and developed with great
success. Evisort allows corporate in-house attorneys, supply chain, and
other professionals to leverage AI to seek patterns in contract data
automatically using content analysis algorithms.
Evisort has offices in Boston and Silicon Valley.
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