Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.

Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A system and method for facilitating execution of a portion of a process via a subprocess. An example method includes encapsulating process logic of a portion of a parent process via the subprocess, wherein the parent process is encoded via a business process language characterized by process lifecycle management functionality; using an instance of a call activity in a scope of the parent process or subprocess to activate the subprocess, yielding a called subprocess in response thereto; and employing a business process runtime engine to adjust a scope of the subprocess to inherit the scope of the process used to call the subprocess, thereby enabling the process lifecycle management functionality to govern a lifecycle of the subprocess. In a more specific embodiment, the business process language includes standard Business Prosecution Execution Language (BPEL); the parent process represents a business process; and the subprocess includes a standalone subprocess.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A system and method for facilitating reuse of a portion of process logic by different processes. An example method includes providing a subprocess that is adapted to perform the process logic in a file accessible to a composite system, wherein the subprocess is adapted to be called by a first parent process via a subprocess extension to a business process language employed to encode the first parent process; using a call activity defined as part of the subprocess extension, and included in a scope of the first parent process to facilitate access to functionality of the subprocess by the parent process; and employing a business process engine to facilitate instantiating the subprocess, resulting in an instantiated subprocess in response thereto; and using a second parent process to share use of the instantiated subprocess with the first parent process.

Abstract: A system and method for enabling reuse of a portion of a business process. An example method includes employing a business process language to facilitate accessing a definition of a subprocess characterizing the process logic, wherein the definition indicates one or more parameters to be used by the subprocess to implement a task specified by the process logic; and employing the definition to facilitate: using one or more variables of a parent process as one or more arguments that are passed to an instantiated version of the subprocess, and mapping the one or more arguments to the one or more parameters. In a more specific embodiment, the example method further includes characterizing a behavior of the subprocess via one or more dynamic scoping rules. The business process language includes a version of Business Process Execution Language (BPEL), and a BPEL extension activity facilitates defining the subprocess.

Abstract: A system and method for facilitating execution of a portion of a process via a subprocess. An example method includes encapsulating process logic of a portion of a parent process via the subprocess, wherein the parent process is encoded via a business process language characterized by process lifecycle management functionality; using an instance of a call activity in a scope of the parent process or subprocess to activate the subprocess, yielding a called subprocess in response thereto; and employing a business process runtime engine to adjust a scope of the subprocess to inherit the scope of the process used to call the subprocess, thereby enabling the process lifecycle management functionality to govern a lifecycle of the subprocess. In a more specific embodiment, the business process language includes standard Business Prosecution Execution Language (BPEL); the parent process represents a business process; and the subprocess includes a standalone subprocess.

Abstract: A system and method for facilitating reuse of a portion of process logic by different processes. An example method includes providing a subprocess that is adapted to perform the process logic in a file accessible to a composite system, wherein the subprocess is adapted to be called by a first parent process via a subprocess extension to a business process language employed to encode the first parent process; using a call activity defined as part of the subprocess extension, and included in a scope of the first parent process to facilitate access to functionality of the subprocess by the parent process; and employing a business process engine to facilitate instantiating the subprocess, resulting in an instantiated subprocess in response thereto; and using a second parent process to share use of the instantiated subprocess with the first parent process.

Abstract: A system and method for managing service interactions launches a process that is defined by a programming abstraction based on a syntax of a general purpose programming language. Interaction with a service, such as a web-based service, is initiated and the process requests the service to perform an action. Execution of the process is suspended until a response is received from the service. Execution of the process continues after receiving a response from the service.

Abstract: A system and method for managing service interactions launches a process that is defined by a programming abstraction based on a syntax of a general purpose programming language. Interaction with a service, such as a web-based service, is initiated and the process requests the service to perform an action. Execution of the process is suspended until a response is received from the service. Execution of the process continues after receiving a response from the service.

Abstract: A system and method for managing service interactions launches a process that is defined by a programming abstraction based on a syntax of a general purpose programming language. Interaction with a service, such as a web-based service, is initiated and the process requests the service to perform an action. Execution of the process is suspended until a response is received from the service. Execution of the process continues after receiving a response from the service.

Abstract: A system and method for managing service interactions launches a process that is defined by a programming abstraction based on a syntax of a general purpose programming language. Interaction with a service, such as a web-based service, is initiated and the process requests the service to perform an action. Execution of the process is suspended until a response is received from the service. Execution of the process continues after receiving a response from the service.