Abstract: A customer who is contacting customer care via a support session regarding a problem is classified into a customer category of multiple customer categories based at least on customer account information of the customer. A customer care topic in a predetermined set of multiple customer care topics that correspond to the problem is then identified via machine learning. A topic script that corresponds to the customer category of the customer for the customer care topic in the predetermined set of customer care topics is further retrieved or generated, in which the topic script includes one or more topic issues related to the customer care topics. The topic script is provided for presentation to a customer service representative (CSR) to prompt the CSR to discuss the one or more topic issues related to the customer care topic with the customer.

Abstract: A customer who is contacting customer care via a support session regarding a problem is classified into a customer category of multiple customer categories based at least on customer account information of the customer. A customer care topic in a predetermined set of multiple customer care topics that correspond to the problem is then identified via machine learning. A topic script that corresponds to the customer category of the customer for the customer care topic in the predetermined set of customer care topics is further retrieved or generated, in which the topic script includes one or more topic issues related to the customer care topics. The topic script is provided for presentation to a customer service representative (CSR) to prompt the CSR to discuss the one or more topic issues related to the customer care topic with the customer.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: This disclosure describes techniques that allow a coach-assist controller to provide coach support to a customer service representative (CSR) during an ongoing consumer-CSR interaction. The coach-assist controller may intercept a consumer-CSR interaction and generate corresponding interaction data. The coach-assist controller may further analyze the interaction data to infer a current state of the consumer-CSR interaction, and in doing so, determine whether to request coach support for the CSR.

Abstract: Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Abstract: This disclosure describes techniques that facilitate selectively interacting with a computing resource based on receipt of an incoming voice command. Particularly, a voice control integration system may parse content of an incoming voice command to authenticate an identity of the client, and further determine an intended meaning of the incoming voice command. In doing so, the voice control integration system may interact with a computing resource to perform an action that fulfills a client request. Computing resources may be associated with service providers or client devices of a client. Further, the voice control integration system may authenticate a client identity based on a one or two-factor authentication protocol, of which one may correspond to a biometric analysis of the incoming voice command. Further, a second-factor of the two-factor authentication protocol may be implemented via a voice interaction device, another client device accessible to the client, or a combination of both.

Abstract: Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Abstract: A customer who is contacting customer care via a support session regarding a problem is classified into a customer category of multiple customer categories based at least on customer account information of the customer. A customer care topic in a predetermined set of multiple customer care topics that correspond to the problem is then identified via machine learning. A topic script that corresponds to the customer category of the customer for the customer care topic in the predetermined set of customer care topics is further retrieved or generated, in which the topic script includes one or more topic issues related to the customer care topics. The topic script is provided for presentation to a customer service representative (CSR) to prompt the CSR to discuss the one or more topic issues related to the customer care topic with the customer.

Abstract: This disclosure describes techniques that facilitate selectively automating a response to a client request for vendor services based on an intended meaning of the client request, a category of vendor services associated with the client request, and one or more factors such as an urgency index and a health index. The vendor services system may parse audio, text, and image data of a client request to determine an intended meaning. In some examples, the vendor services system may automate a response that resolves the client request, or automate a response that requests additional information from the client device. Alternatively, or additionally, the vendor services system may direct the client request to a vendor representative for further processing. In doing so, the vendor services system may monitor dialogue between the client and vendor representative, and selectively provide the vendor representative with support data that may help resolve the client request.

Abstract: This disclosure describes techniques that facilitate selectively automating a response to a client request for vendor services based on an intended meaning of the client request, a category of vendor services associated with the client request, and one or more factors such as an urgency index and a health index. The vendor services system may parse audio, text, and image data of a client request to determine an intended meaning. In some examples, the vendor services system may automate a response that resolves the client request, or automate a response that requests additional information from the client device. Alternatively, or additionally, the vendor services system may direct the client request to a vendor representative for further processing. In doing so, the vendor services system may monitor dialogue between the client and vendor representative, and selectively provide the vendor representative with support data that may help resolve the client request.

Abstract: Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Abstract: This disclosure describes techniques that allow a coach-assist controller to provide coach support to a customer service representative (CSR) during an ongoing consumer-CSR interaction. The coach-assist controller may intercept a consumer-CSR interaction and generate corresponding interaction data. The coach-assist controller may further analyze the interaction data to infer a current state of the consumer-CSR interaction, and in doing so, determine whether to request coach support for the CSR.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: This disclosure describes techniques that facilitate selectively automating a response to a client request for vendor services based on an intended meaning of the client request, a category of vendor services associated with the client request, and one or more factors such as an urgency index and a health index. The vendor services system may parse audio, text, and image data of a client request to determine an intended meaning. In some examples, the vendor services system may automate a response that resolves the client request, or automate a response that requests additional information from the client device. Alternatively, or additionally, the vendor services system may direct the client request to a vendor representative for further processing. In doing so, the vendor services system may monitor dialogue between the client and vendor representative, and selectively provide the vendor representative with support data that may help resolve the client request.

Abstract: This disclosure sets forth systems and techniques that integrates social networking services with vendor services, such that a user may directly or indirectly communicate their experience, impression, or intention to a vendor via a user's preferred social networking service. In some examples, the social networking services may facilitate a vendor providing technical service support for a product or service. In other examples, a user may initiate a transaction with the vendor via a preferred social networking service. The user may initiate payment for an outstanding bill, initiate a purchase of vendor products or services, solicit a trade-in estimate for a particular product, query an order status, or initiate a data-allowance transfer to a recipient of a telecommunications vendor. In each of these examples, the user may communicate with a vendor by via social media posts on a social networking services authorized via a vendor platform.

Abstract: A helical-bladed cutting reel includes a central shaft having a central axis of rotation, and a plurality of helical blades. Each of the blades extends along a respective helical path on an outer surface of the central shaft. A direction of each respective helical path has both an axial component and a circumferential component relative to the central axis of the central shaft as it extends across the outer surface of the central shaft. Each of the helical blades is welded directly to the central shaft. In preferred embodiments all of the blades are continuously autogenously welded directly to the central shaft.

Abstract: This disclosure describes techniques that facilitate selectively interacting with a computing resource based on receipt of an incoming voice command. Particularly, a voice control integration system may parse content of an incoming voice command to authenticate an identity of the client, and further determine an intended meaning of the incoming voice command. In doing so, the voice control integration system may interact with a computing resource to perform an action that fulfills a client request. Computing resources may be associated with service providers or client devices of a client. Further, the voice control integration system may authenticate a client identity based on a one or two-factor authentication protocol, of which one may correspond to a biometric analysis of the incoming voice command. Further, a second-factor of the two-factor authentication protocol may be implemented via a voice interaction device, another client device accessible to the client, or a combination of both.

Abstract: This disclosure describes techniques that facilitate selectively interacting with a computing resource based on receipt of an incoming voice command. Particularly, a voice control integration system may parse content of an incoming voice command to authenticate an identity of the client, and further determine an intended meaning of the incoming voice command. In doing so, the voice control integration system may interact with a computing resource to perform an action that fulfills a client request. Computing resources may be associated with service providers or client devices of a client. Further, the voice control integration system may authenticate a client identity based on a one or two-factor authentication protocol, of which one may correspond to a biometric analysis of the incoming voice command. Further, a second-factor of the two-factor authentication protocol may be implemented via a voice interaction device, another client device accessible to the client, or a combination of both.