Abstract: Intent-based automation that discovers automatable tasks and/or determines task variants in data is disclosed. Task capture data may be utilized to determine task variants in task mining data. Semantic understanding of user actions by artificial intelligence (AI)/machine learning (ML) model(s), for example, may be applied to determine the intent of the user rather than only focusing on what actions the user is performing on the computing system. Application logs and semantic understanding may be used to facilitate a more accurate determination of what the user actually intends to do. Task capture for individual user flows may be performed. Once these are captured, task capture algorithms and AI/ML models are used to determine which parts of the flows are similar and/or match and which parts are unique. The path through these flows can then be followed to build a process graph that includes decision points representing the unique flows.

Abstract: Systems and methods for identifying patterns of sequences of actions for performing a task from task execution data are provided. The task execution data of user interaction with a computing system for performing the task is received. A task graph is generated based on the task execution data. Patterns of sequences of actions for performing the task are identified based on the task graph. The identified patterns are output.

Abstract: Systems and methods for providing insights on data of various platforms are provided. One or more requests for insights on data of at least one of an automation platform, a process mining platform, or a task mining platform are received. In response to receiving the one or more requests, a response comprising the insights is generated using a language model that was trained using training data of one or more automation platforms, one or more process mining platforms, and one or more task mining platforms. The response is output.

Abstract: A method is provided. The method is executed by an interface engine implemented as a computer program within a computing environment. The interface engine executes detection and automation of computer activity. The method includes recording the computer activity across user interfaces (UIs) and automatically processing the computer activity utilizing a generative AI model to extract patterns. The patterns include portions of the computer activity that are similar or resilient to changes. The method includes determining existing automations according to the patterns.

Abstract: A method is provided. The method is executed by an extraction engine implemented as a computer program within a computing environment. The extraction engine executes action and task mining on unstructured data. The method includes receiving a communication including unstructured data defining an action and automatically processing the communication by utilizing at least one generative artificial intelligence (AI) model to extract details of the action being performed in the unstructured data. The method includes automatically converting the action into an activity or a task of a process associated with the communication.

Abstract: A method is disclosed. The method is implemented by a robot engine that is stored as program code on a memory of a system. The program code is executed by a processor of the system, which enables robotic process automations of the robot engine. The processor is communicatively coupled to the memory within the system. The method includes initiating a guided operation of a platform presented by the system and monitoring the guided operation to observe an interaction with the platform or to receive a direct input by the robot engine. The method also includes executing a backend operation with respect to the interaction or the direct input.

Abstract: Systems and methods are provided for determining variants of an automatable task. Task flow data of a performance of an automatable task by one or more users is received. The task flow data is generated based on user input using task mining. User interaction data is identified from the task flow data. One or more variants of the automatable task are determined based on the user interaction data using a machine learning based model. The one or more variants of the automatable task are output.

Abstract: Systems and methods are provided for merging task graphs representing variants of an automatable task into a merged task graph. A plurality of task graphs each representing a variant of an automatable task is received. Similarities between the plurality of task graphs are identified. The plurality of task graphs is merged into a merged task graph of the automatable task based on the identified similarities. The merged task graph is output.

Abstract: Systems and methods are provided for determining variants of an automatable task. Task flow data of a performance of an automatable task by one or more users is received. The task flow data is generated based on user input using task mining. User interaction data is identified from the task flow data. One or more variants of the automatable task are determined based on the user interaction data using a machine learning based model. The one or more variants of the automatable task are output.

Abstract: Systems and methods are provided for merging task graphs representing variants of an automatable task into a merged task graph. A plurality of task graphs each representing a variant of an automatable task is received. Similarities between the plurality of task graphs are identified. The plurality of task graphs is merged into a merged task graph of the automatable task based on the identified similarities. The merged task graph is output.

Abstract: In one embodiment, in an information processing apparatus, comprising at least one computer processor, a Bot executed by the at least one computer processor may perform the following: (1) receiving invoice information for an invoice for a payor, the invoice information comprising an invoice amount and a due date; (2) electronically communicating a payment reminder comprising the invoice amount and the due date to the payor in a chat interface; and (3) providing a payment interface in the chat interface.

Abstract: Intent-based automation that discovers automatable tasks and/or determines task variants in data is disclosed. Task capture data may be utilized to determine task variants in task mining data. Semantic understanding of user actions by artificial intelligence (AI)/machine learning (ML) model(s), for example, may be applied to determine the intent of the user rather than only focusing on what actions the user is performing on the computing system. Application logs and semantic understanding may be used to facilitate a more accurate determination of what the user actually intends to do. Task capture for individual user flows may be performed. Once these are captured, task capture algorithms and AI/ML models are used to determine which parts of the flows are similar and/or match and which parts are unique. The path through these flows can then be followed to build a process graph that includes decision points representing the unique flows.

Abstract: Trigger(s) administration, development, distribution, coordination, registration, or coding for a software automation process or robotic process automation (RPA) is disclosed. A trigger(s) may be configured to run or execute by an outside service or component for an automation process in relation to an application and associated event(s). A definition file(s) or configuration file(s) may be created or utilized for a trigger(s) for an event. A separate or outside service or component may be configured to listen for the event in the process. Once a trigger(s) is met, an action or activity may run for the automation process on a client device using the outside service or component.

Abstract: In one embodiment, in an information processing apparatus, comprising at least one computer processor, a Bot executed by the at least one computer processor may perform the following: (1) receiving invoice information for an invoice for a payor, the invoice information comprising an invoice amount and a due date; (2) electronically communicating a payment reminder comprising the invoice amount and the due date to the payor in a chat interface; and (3) providing a payment interface in the chat interface.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.

Abstract: In one embodiment, in an information processing apparatus, comprising at least one computer processor, a Bot executed by the at least one computer processor may perform the following: (1) receiving invoice information for an invoice for a payor, the invoice information comprising an invoice amount and a due date; (2) electronically communicating a payment reminder comprising the invoice amount and the due date to the payor in a chat interface; and (3) providing a payment interface in the chat interface.

Abstract: Application integration for robotic process automation (RPA) using a development application configured for development of RPA-enabled applications is disclosed. The development application in some embodiments may be used for application integration with attended robots that execute locally on the same computing system as an instance of the RPA-enabled application, unattended robots that execute on a remote computing system, or both, creating an RPA-enabled application. One or more user interface (UI) elements, variables, and/or events of an RPA-enabled application may be linked to one or more respective RPA processes, causing respective RPA robot(s) to carry out the associated functionality.

Abstract: A method is disclosed. The method is implemented by a robot engine that is stored as program code on a memory of a system. The program code is executed by a processor of the system, which enables robotic process automations of the robot engine. The processor is communicatively coupled to the memory within the system. The method includes initiating a guided operation of a platform presented by the system and monitoring the guided operation to observe an interaction with the platform or to receive a direct input by the robot engine. The method also includes executing a backend operation with respect to the interaction or the direct input.

Abstract: Application integration for robotic process automation (RPA) using a development application configured for development of RPA-enabled applications is disclosed. The development application in some embodiments may be used for application integration with attended robots that execute locally on the same computing system as an instance of the RPA-enabled application, unattended robots that execute on a remote computing system, or both, creating an RPA-enabled application. One or more user interface (UI) elements, variables, and/or events of an RPA-enabled application may be linked to one or more respective RPA processes, causing respective RPA robot(s) to carry out the associated functionality.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.