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Starting Today, Columbia’s Professor
Daniel Guetta Uses Evisort to Teach
Text Mining in New Artificial
Intelligence MBA Course
Businesswire.com
Starting Today, Columbia’s Professor Daniel Guetta Uses
Evisort to Teach Text Mining in New Artificial Intelligence
MBA Course
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 about Evisort, 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 time significantly.”
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 of data.”
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.
Starting Today, Columbia Professor Daniel Guetta Uses Evisort to Teach Text Mining in New Artificial Intelligence Mba Course

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Starting Today, Columbia Professor Daniel Guetta Uses Evisort to Teach Text Mining in New Artificial Intelligence Mba Course

  • 1. Starting Today, Columbia’s Professor Daniel Guetta Uses Evisort to Teach Text Mining in New Artificial Intelligence MBA Course Businesswire.com
  • 2. Starting Today, Columbia’s Professor Daniel Guetta Uses Evisort to Teach Text Mining in New Artificial Intelligence MBA Course 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 about Evisort, 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.”
  • 3. 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 time significantly.” 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 of data.” 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.