Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effective for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.

Abstract: Disclosed communication flow modeling solution is significantly streamlined in a user friendly way to shield users from the technical complexities usually required. At design time, an orchestration flow modeling application receives user instruction to open or create a communication flow modeling project. Per configuration specific to an enterprise associated with the user, a custom drag-and-drop communication flow modeling environment with a canvas and modeling entities is provided. Responsive to the user dragging and dropping a set of modeling entities from the menu onto the communication flow modeling canvas and drawing connections between them, the orchestration flow modeling application logically connects the modeling entities to form a valid communication flow and stores it in a database. The communication flow undergoes an approval process. Once approved, it is activated for execution by an orchestration server.