SCREEN-POP CONFIGURATION USING FLOW BUILDER APPLICATION

    公开(公告)号:US20230161607A1

    公开(公告)日:2023-05-25

    申请号:US17456366

    申请日:2021-11-23

    CPC classification number: G06F9/451 G06F8/34 G06F16/9038 G06Q30/016

    Abstract: Methods, systems, apparatuses, devices, and computer program products are described. An application server may receive a set of parameters for configuring a user interface screen-pop for an application via a user input of a flow builder application. The screen-pop may include a visual feature that appears in a user interface of the application in response to a trigger. The application server may store instructions for implementing the screen-pop as a process flow according to the flow builder application and execute the process flow in response to receiving an indication of the trigger from the application, and in accordance with metadata associated with the trigger. In some examples, the application server may store the output of the process flow execution in a database and query the database for the instructions. The application server may send instructions for displaying the screen-pop to the application based on the indication of the trigger.

    DYNAMIC FIELD VALUE RECOMMENDATION METHODS AND SYSTEMS

    公开(公告)号:US20210149933A1

    公开(公告)日:2021-05-20

    申请号:US15929364

    申请日:2020-04-28

    Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.

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