Abstract: An AI-based process monitoring system access a plurality of data sources having different data formats to collect and analyze KPI data and shortlist KPIs that are to be used for determining the impact of automation of an automated process or sub-process. Information regarding an automated process is received and KPIs associated with the process and sub-processes of the process are identified. The identified KPIs are put through an approval process and the approved KPIs are presented to a user for selection. The user-selected KPIs are evaluated based on classification, ranking and sentiments associated therewith. The evaluations are again presented to the user along with a set of questionnaires wherein each of the questions has a dynamically controlled weight associated therewith. Based at least on the weights and user responses, a subset of the evaluated KPIs are shortlisted for use in evaluating the impact of process automation.

Abstract: A productivity measuring, modeling and illustrating system receives input data pertaining to the productivity of an organization to generate various productivity views using a productivity maturity model. The productivity maturity model is based on suggested actions for increasing the productivity which are received in the input data. The productivity maturity model computes various productivity gains and provides productivity levels for the productivity levers associated with the organization. Various productivity views generated to display the productivity information include a summary view that displays the productivity gains and productivity levels using different filters.

Abstract: An AI-based process monitoring system access a plurality of data sources having different data formats to collect and analyze KPI data and shortlist KPIs that are to be used for determining the impact of automation of an automated process or sub-process. Information regarding an automated process is received and KPIs associated with the process and sub-processes of the process are identified. The identified KPIs are put through an approval process and the approved KPIs are presented to a user for selection. The user-selected KPIs are evaluated based on classification, ranking and sentiments associated therewith. The evaluations are again presented to the user along with a set of questionnaires wherein each of the questions has a dynamically controlled weight associated therewith. Based at least on the weights and user responses, a subset of the evaluated KPIs are shortlisted for use in evaluating the impact of process automation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, a using a bot management framework to provide bot management solutions for software bots deployed in a robotic process automation (RPA) system. In one aspect, a method includes the actions of receiving, from a RPA system, information regarding a software bot deployed within the RPA system to perform an assigned task, the information including incident data from an anomaly in the RPA system while the software bot performed the assigned task; mapping the received incident data according to a common data model; determining a resolution for the anomaly based an analysis through a trained artificial intelligence model of the mapped incident data; and executing the determined resolution.

Abstract: A device may obtain a document, of a document type, from which specific information is to be captured. The specific information to be captured may depend on a document class associated with the document. The device may identify the document class, associated with the document, based on a characteristic of the document. The document class may identify a category of document in which the document is included, and may be associated with multiple document types. The device may determine field information associated with the document class. The field information may include information that identifies a portion of the document where the specific information is located, or may include information that identifies a manner in which the specific information can be identified within the document. The device may analyze the document, based on the field information, in order to capture the specific information. The device may provide the captured specific information.

Abstract: A productivity measuring, modeling and illustrating system receives input data pertaining to the productivity of an organization to generate various productivity views using a productivity maturity model. The productivity maturity model is based on suggested actions for increasing the productivity which are received in the input data. The productivity maturity model computes various productivity gains and provides productivity levels for the productivity levers associated with the organization. Various productivity views generated to display the productivity information include a summary view that displays the productivity gains and productivity levels using different filters.

Abstract: A device may obtain a document, of a document type, from which specific information is to be captured. The specific information to be captured may depend on a document class associated with the document. The device may identify the document class, associated with the document, based on a characteristic of the document. The document class may identify a category of document in which the document is included, and may be associated with multiple document types. The device may determine field information associated with the document class. The field information may include information that identifies a portion of the document where the specific information is located, or may include information that identifies a manner in which the specific information can be identified within the document. The device may analyze the document, based on the field information, in order to capture the specific information. The device may provide the captured specific information.