Abstract: A computer-based method for managing a dataflow pipeline across a plurality of environments, includes the steps of: receiving, for a first environment, a check-in comprising source code, a task definition, a configuration, and a flow definition; receiving a definition of an application secret and an associated credential; storing the application secret and credential in a dataflow pipeline deployer data store; creating a data flow pipeline package, further comprising the steps of: merging the source code, the configuration, and the secrets; and defining a pipeline graph in the first environment pipeline flow registry.

Abstract: A ranking of customer service interactions sessions that may benefit from supervisor input is provided. The customer service interactions sessions involve a Customer Service Representative (CSR), engaged in a customer service interaction with a customer. First, customer service interaction sessions, at a contact center server, between the CSRs and the customers begin. Data streams from CSR computer(s) to customer computer(s) are sent. Other data streams from the customer computers are received. The data streams are analyzed by a supervisor recommendation engine. Based on the analysis, the supervisor recommendation engine generates a ranking of customer service interactions sessions that would benefit most from supervisor input.

Abstract: A ranking of customer service interactions sessions that may benefit from supervisor input is provided. The customer service interactions sessions involve a Customer Service Representative (CSR), engaged in a customer service interaction with a customer. First, customer service interaction sessions, at a contact center server, between the CSRs and the customers begin. Data streams from CSR computer(s) to customer computer(s) are sent. Other data streams from the customer computers are received. The data streams are analyzed by a supervisor recommendation engine. Based on the analysis, the supervisor recommendation engine generates a ranking of customer service interactions sessions that would benefit most from supervisor input.

Abstract: Automated whisper coaching for a Customer Service Representative (CSR), engaged in a customer service interaction with a customer, is provided. First, a customer service interaction session, at a contact center server, between the CSR and the customer begins. A first data stream from a CSR computer to a customer computer is sent. A second data stream from the customer computer is received. The first data stream and the second data stream are analyzed by a supervisor BOT. Based on the analysis, the supervisor BOT provides automated whisper coaching to the CSR computer.

Abstract: Systems, methods, and computer-readable media for providing domain-specific type-ahead suggestions in a chat. In some embodiments, a method can include connecting a first user to communicate with a second user in a chat session. A first user-specific type-ahead domain for the second user can be selected based on one or more characteristics associated with the first user. The method can include receiving message input from the second user in the first chat session and selecting a first user-specific type-ahead suggestion for the second user based on the message input and the one or more characteristics associated with the first user using the first user-specific type-ahead domain. Subsequently, the first user-specific type-ahead suggestion can be presented to the first user if the second user accepts the first user-specific type-ahead suggestion.

Abstract: Systems, methods, and computer-readable media for providing domain-specific type-ahead suggestions in a chat. In some embodiments, a method can include connecting a first user to communicate with a second user in a chat session. A first user-specific type-ahead domain for the second user can be selected based on one or more characteristics associated with the first user. The method can include receiving message input from the second user in the first chat session and selecting a first user-specific type-ahead suggestion for the second user based on the message input and the one or more characteristics associated with the first user using the first user-specific type-ahead domain. Subsequently, the first user-specific type-ahead suggestion can be presented to the first user if the second user accepts the first user-specific type-ahead suggestion.