Abstract: Dynamically updating, or retraining and updating, artificial intelligence (AI)/machine learning (ML) models in digital processes at runtime is disclosed. Production operation may not need to be stopped for AI/ML model update or retraining and update. The update steps and/or retraining steps for the AI/ML model may be included as part of the digital process. The AI/ML model update may be requested from internal logic (e.g., from the evaluation of a condition, by an expression that calls for the AI/ML model, etc.), external requests (e.g., from external triggers in a finite state machine (FSM), such as a file change, database data, a service call, etc.), or both. Automation of AI/ML model updates or retraining and updates may be provided, where the software reloads/reinitializes/re-instantiates with a retrained and/or updated AI/ML model after (and possibly immediately after) the AI/ML model becomes available.

Abstract: Dynamically updating, or retraining and updating, artificial intelligence (AI)/machine learning (ML) models in digital processes at runtime is disclosed. Production operation may not need to be stopped for AI/ML model update or retraining and update. The update steps and/or retraining steps for the AI/ML model may be included as part of the digital process. The AI/ML model update may be requested from internal logic (e.g., from the evaluation of a condition, by an that expression calls for the AI/ML model, etc.), external requests (e.g., from external triggers in a finite state machine (FSM), such as a file change, database data, a service call, etc.), or both. Automation of AI/ML model updates or retraining and updates may be provided, where the software reloads/reinitializes/re-instantiates with a retrained and/or updated AI/ML model after (and possibly immediately after) the AI/ML model becomes available.

Abstract: Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.

Abstract: Dynamically updating, or retraining and updating, artificial intelligence (AI)/machine learning (ML) models in digital processes at runtime is disclosed. Production operation may not need to be stopped for AI/ML model update or retraining and update. The update steps and/or retraining steps for the AWL model may be included as part of the digital process. The AI/ML model update may be requested from internal logic (e.g., from the evaluation of a condition, by an that expression calls for the AI/ML model, etc.), external requests (e.g., from external triggers in a finite state machine (FSM), such as a file change, database data, a service call, etc.), or both. Automation of AI/ML model updates or retraining and updates may be provided, where the software reloads/reinitializes/re-instantiates with a retrained and/or updated AWL model after (and possibly immediately after) the AI/ML model becomes available.

Abstract: A method and system which provides for generating an integrated report. The method and system utilize information in a data storage system to provide individual account holders with an integrated report which includes detailed information regarding the financial account, and integrates financial planning recommendation information with the information regarding the financial account. Typically, the information regarding the financial account will be of sufficient detail so that a separate account statement need not be sent to the individual. The system and method herein provide individual account holders with a single report which provides the individual with financial account information, and financial planning advice, utilizing data available in a data storage system. Thus, the individual need not seek out advice, rather it is proactively delivered to the individual.

Abstract: A method and system which provides for generating an integrated report. The method and system utilize information in a data storage system to provide individual account holders with an integrated report which includes detailed information regarding the financial account, and integrates financial planning recommendation information with the information regarding the financial account. Typically, the information regarding the financial account will be of sufficient detail so that a separate account statement need not be sent to the individual. The system and method herein provide individual account holders with a single report which provides the individual with financial account information, and financial planning advice, utilizing data available in a data storage system. Thus, the individual need not seek out advice, rather it is proactively delivered to the individual.

Abstract: A method and system which provides for generating an integrated report. The method and system utilize information in a data storage system to provide individual account holders with an integrated report which includes detailed information regarding the financial account, and integrates financial planning recommendation information with the information regarding the financial account. Typically, the information regarding the financial account will be of sufficient detail so that a separate account statement need not be sent to the individual. The system and method herein provide individual account holders with a single report which provides the individual with financial account information, and financial planning advice, utilizing data available in a data storage system. Thus, the individual need not seek out advice, rather it is proactively delivered to the individual.