Abstract: The example embodiments are directed to systems and methods which can generate a process graph with important process insights in a manner that is significantly faster and more scalable than related art approaches and answers questions most customers have through the use of standardization. In one example, a method may include querying a data store for document data of a process, identifying a plurality of milestones that occur within the process and blockers that prevent at least one of the milestones from completing based on the document data, generating a graph model of the process based on a predefined template, wherein the graph model comprises a plurality of nodes corresponding to the plurality of milestones and edges between the plurality of nodes based on the blockers, and displaying the graph model of the process via a user interface.

Abstract: The example embodiments are directed to systems and methods which may provide a guided user interface session for user input to a software process based on annotations added to a process model of the software process. In one example, a method may include receiving runtime data of an instance of software process from a workflow engine that is executing the instance of the software process, determining a process activity that is excepted to happen next within the running instance of the software process, identifying GUI and a subset of input elements within the GUI which are mapped to the determined process activity based on annotations within a process model of the software process, highlighting the identified subset of input elements and disabling any remaining input elements within the GUI to generate a guided GUI, and displaying the guided GUI via a computing system of a user.

Abstract: The example embodiments are directed to systems and methods which can generate a process graph with important process insights in a manner that is significantly faster and more scalable than related art approaches and answers questions most customers have through the use of standardization. In one example, a method may include querying a data store for document data of a process, identifying a plurality of milestones that occur within the process and blockers that prevent at least one of the milestones from completing based on the document data, generating a graph model of the process based on a predefined template, wherein the graph model comprises a plurality of nodes corresponding to the plurality of milestones and edges between the plurality of nodes based on the blockers, and displaying the graph model of the process via a user interface.

Abstract: Data is gathered from a log file on a first application server, a log file on a second application server, a database on a database server, or any suitable combination thereof. By correlating the data from different sources, XP-Functions that execute in sequence on a single application server are identified and combined into a sequence referred to as an executable process chain (XP-Chain). The automatic process discovery server reconstructs end-to-end processes out of XP-Chains, even when the XP-Chains are executed on different application servers, based on log files and database data. A test script may be generated for an identified end-to-end process. By running the test script, proper functioning of the end-to-end process may be confirmed. Existing test scripts may be disabled for a formerly identified end-to-end process that is no longer found to be executed.

Abstract: The example embodiments are directed to systems and methods which can generate process insights in a manner that is significantly faster than process mining. In one example, a method may include loading a schema of a data system into memory, identifying a plurality of events that occur within a process supported by data from the data system and a plurality of blockers that prevent the plurality of events from completing, defining a query that comprises instructions for extracting data of the plurality of blockers from the data system and for analyzing the process based on the extracted data and the plurality of blockers, and generating a script for executing the defined query based on the schema of the data system and transmit the script to a software application.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the bot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the bot generation server generates a bot to automate some or all of the process step.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the hot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the hot generation server generates a bot to automate some or all of the process step.

Abstract: Provided are systems and methods for creating and managing an interactive process graphs which expedite performance of a multi-user enterprise process between user interfaces and the underlying systems. In one example, a method may include generating a process graph of a user interface process, wherein the process graph comprises nodes corresponding to activities and vertices between the nodes identifying dependencies among the activities, embedding input fields in the nodes of the process graph, embedding, via the process graph, an identifier of a current location of a data object within an instance within the user interface process, and displaying an instance of the process graph corresponding to the instance of the user interface process which includes the embedded input fields in the nodes and the identifier of the current location of the data object within the instance of the user interface process.

Abstract: The present application is directed to a system which offers a turnkey solution (BPaaS) for running an organization business process via a third-party provider. In one example, the method may include generating a first plurality of finite state automata corresponding to a plurality of event sequences of a software process of a user, obtaining a second plurality of finite state automata based on a second plurality of event sequences of a host process of a provider, establishing channels of communication between the first and second plurality of finite state automata, executing the first and second plurality of finite state automata in parallel via the established channels, and determining whether the user process is compatible with the host process of the provider based on results of the execution, and displaying a result of the determination via a user interface of a computing system associated with the user.

Abstract: Provided are systems and methods for creating and managing an interactive process graphs which expedite performance of a multi-user enterprise process between user interfaces and the underlying systems. In one example, a method may include generating a process graph of a user interface process, wherein the process graph comprises nodes corresponding to activities and vertices between the nodes identifying dependencies among the activities, embedding input fields in the nodes of the process graph, embedding, via the process graph, an identifier of a current location of a data object within an instance within the user interface process, and displaying an instance of the process graph corresponding to the instance of the user interface process which includes the embedded input fields in the nodes and the identifier of the current location of the data object within the instance of the user interface process.

Abstract: Data is gathered from a log file on a first application server, a log file on a second application server, a database on a database server, or any suitable combination thereof. By correlating the data from different sources, XP-Functions that execute in sequence on a single application server are identified and combined into a sequence referred to as an executable process chain (XP-Chain). The automatic process discovery server reconstructs end-to-end processes out of XP-Chains, even when the XP-Chains are executed on different application servers, based on log files and database data. A test script may be generated for an identified end-to-end process. By running the test script, proper functioning of the end-to-end process may be confirmed. Existing test scripts may be disabled for a formerly identified end-to-end process that is no longer found to be executed.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the bot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the bot generation server generates a bot to automate some or all of the process step.

Abstract: Information about time consumed in a task is combined with employment data about users performing the task to determine an associated cost of time. Based on the cost of performing the task and a predicted cost of automating the task, a predicted savings resulting from automation of the task is determined. From among multiple processes that are available to be automated, a recommendation is made to automate the task that benefits from the greatest savings. A user interface may be presented that identifies multiple processes and the automation savings available for each one. In response to an interaction with the user interface, bots are generated to automate the steps of a process.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the bot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the bot generation server generates a bot to automate some or all of the process step.

Abstract: An application server provides an application to client devices. Users of the client devices interact with the application to perform a business process. Data regarding user interactions with the application is transmitted from the client devices to the application server. Based on an analysis of the received data, a bot generation server generates a bot to automate a process step. The bot generation server provides a heatmap user interface (UI) that provides information regarding the process steps. Using the heatmap UI, the administrator selects a process step for automation. In response to the selection, the bot generation server identifies, based on the observed behavior, relationships between input fields, typical values for input fields, typical order of data entry into input fields, or any suitable combination thereof. Based on the identified patterns, the bot generation server generates a bot to automate some or all of the process step.

Abstract: An application server provides an application or set of applications to one or more client devices. One or more users of the client devices interact with the applications to perform a business process. Data is stored on one or more of the client devices that tracks user interactions with the application. The data is transmitted from the client devices to the application server for analysis. Data from multiple client devices is correlated to enable analysis of a complex business process. As a result of the analysis, bottlenecks may be identified based on a particular process step taking a long time to complete or receiving repeated re-entry of data. The solution is automated and scalable, allowing for analysis of an entire business process landscape.

Abstract: An application server provides an application or set of applications to one or more client devices. One or more users of the client devices interact with the applications to perform a business process. Data is stored on one or more of the client devices that tracks user interactions with the application. The data is transmitted from the client devices to the application server for analysis. Data from multiple client devices is correlated to enable analysis of a complex business process. As a result of the analysis, bottlenecks may be identified based on a particular process step taking a long time to complete or receiving repeated re-entry of data. The solution is automated and scalable, allowing for analysis of an entire business process landscape.