Abstract: A system and method for regulatory compliance management are disclosed. The method includes receiving, by the at least one processor, at least one regulatory document from at least one regulatory source. Further, the method includes analyzing, by the at least one processor using a trained model, the at least one regulatory document. Further, the method includes drafting, by the at least one processor, an obligation for at least one entity based on the analysis of the at least one regulatory document. Further, the method includes mapping, by the at least one processor, an information in the obligation to at least one of a set of internal procedures and policies of the at least one entity. Further, the method includes updating, by the at least one processor, the internal procedures and policies of the at least one entity to maintain a legal compliance with the obligation.

Abstract: A method and a system for extracting information from a table in a document is provided. The method includes: receiving a document that includes information that is arranged in a table; determining three sets of coordinates that respectively relate to lines, words, and characters included in the document; extracting a list of lines based on the first set of coordinates; reconstructing the rows of the table based on list of lines and the second set of coordinates; reconstructing the columns of the table based on the reconstructed rows and the third set of coordinates; and outputting a reconstruction of the table. The three sets of coordinates are expressible in an hOCR format that is based on an open standard for representation of scanned information that is obtainable by using an optical character recognition (OCR) technique.

Abstract: A method and a system for extracting information from a table in a document is provided. The method includes: receiving a document that includes information that is arranged in a table; determining three sets of coordinates that respectively relate to lines, words, and characters included in the document; extracting a list of lines based on the first set of coordinates; reconstructing the rows of the table based on list of lines and the second set of coordinates; reconstructing the columns of the table based on the reconstructed rows and the third set of coordinates; and outputting a reconstruction of the table. The three sets of coordinates are expressible in an hOCR format that is based on an open standard for representation of scanned information that is obtainable by using an optical character recognition (OCR) technique.

Abstract: A method and a system for extracting information from a table in a document is provided. The method includes: receiving a document that includes information that is arranged in a table; determining three sets of coordinates that respectively relate to lines, words, and characters included in the document; extracting a list of lines based on the first set of coordinates; reconstructing the rows of the table based on list of lines and the second set of coordinates; reconstructing the columns of the table based on the reconstructed rows and the third set of coordinates; and outputting a reconstruction of the table. The three sets of coordinates are expressible in an hOCR format that is based on an open standard for representation of scanned information that is obtainable by using an optical character recognition (OCR) technique.

Abstract: Systems and methods for Bot automation lifecycle management are disclosed. According to one embodiment, in an information processing apparatus comprising at least one computer processor, a method for Bot automation lifecycle management may include: (1) receiving information on a proposed automation process; (2) using the information, calculating a complexity score, an automation time requirement, an automation cost, an automation efficiency, and a Bot requirement; (3) calculating a feasibility score based on the complexity score, the automation time requirement, the automation cost, the automation efficiency, and the Bot requirement; (4) generating a feasibility report based on the feasibility score; (5) exporting the proposed automation process to a build process; and (6) confirming the build process as complete and assessing an actual complexity score, an actual automation time requirement, an actual automation cost, an actual automation efficiency, and an actual Bot requirement.

Abstract: A method and a system for extracting information from a table in a document is provided. The method includes: receiving a document that includes information that is arranged in a table; determining three sets of coordinates that respectively relate to lines, words, and characters included in the document; extracting a list of lines based on the first set of coordinates; reconstructing the rows of the table based on list of lines and the second set of coordinates; reconstructing the columns of the table based on the reconstructed rows and the third set of coordinates; and outputting a reconstruction of the table. The three sets of coordinates are expressible in an hOCR format that is based on an open standard for representation of scanned information that is obtainable by using an optical character recognition (OCR) technique.

Abstract: Systems and methods for Bot automation lifecycle management are disclosed. According to one embodiment, in an information processing apparatus comprising at least one computer processor, a method for Bot automation lifecycle management may include: (1) receiving information on a proposed automation process; (2) using the information, calculating a complexity score, an automation time requirement, an automation cost, an automation efficiency, and a Bot requirement; (3) calculating a feasibility score based on the complexity score, the automation time requirement, the automation cost, the automation efficiency, and the Bot requirement; (4) generating a feasibility report based on the feasibility score; (5) exporting the proposed automation process to a build process; and (6) confirming the build process as complete and assessing an actual complexity score, an actual automation time requirement, an actual automation cost, an actual automation efficiency, and an actual Bot requirement.