Smart Legal Contract Migration using Machine Learning

Most modern enterprise contract management systems deal with thousands of contracts. These applications are built to operate inclusively, i.e. preparing the contracts or editing the existing contracts within the application is quite easy. But, organizations also deal with various types of contracts outside such systems. Individuals working in the legal domain work on contracts stored mostly in word, pdf format. They usually work on these documents to generate various versions of the contracts. But sometimes, there exist physical contracts in the form of printed documents which needs to be digitized and fed into the system. If a contract management system provides the functionality of editing such contracts in the application, it poses a great challenge for the user to get them into the application, which might involve manual entry of contract from a physical document, copy/paste of content from a word/pdf file into the application. There exists no such intelligence to extract these clauses/content from physical documents, classify them with respect to many parameters such as applicable governing laws, the type of content present in the clauses such as Lease agreement, Sale deed, etc. and finally reuse them by having such clauses in a clause library. This smartness needs to be introduced into any CMS systems for seamless contract migration.