Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Systems and methods are disclosed herein for device selection and modified output upon receiving notifications. In one embodiment of the disclosed technique for selecting an output device for notifications, systems and methods receive an electronic notification which indicate an originator of the electronic notification. An output range is determined for each electronic device in a plurality of electronic devices. The system selects the electronic device with the smallest of determined output ranges from the plurality of electronic devices. The system determines from the indication whether the originator of the electronic notification is on a stored list of originators. If so, the system transmits the electronic notification to the selected electronic device for output.

Aspects of the present disclosure relate to systems and methods that aid users with hearing and/or speech impediments to have a conversation with a remote phone number without human assistance. In one aspect, an application residing on a user's device, such as a smartphone, tablet computer, laptop, etc., may be used to initiate a phone call to a recipient. Upon initiating the phone call locally, a service residing on the server may receive a request to initiate a connection to the recipient. Once the recipient answers, the user may converse with the recipient by providing text input to their local app. The text input may be transmitted to the service. The service may use a text to speech converter to translate the received text to speech that can be delivered to the recipient.

A third-party service may be used to assist entities in responding to requests of users by determining a suggested response to a received communication. The third party service may receive a request from a first entity, such as via an application programming interface request, that includes a message in a conversation. A conversation feature vector may be computed by processing the message with a first neural network. A suggested respond to the message may be determined by processing the conversation feature vector with a second neural network. The third-party service may then return the suggested response for use in the conversation. The third-party service may similarly be used to assist other entities in responding to requests of users.

A method performed by, and a system embedded within, a communication device operating in a communication network, performing the steps of: obtaining a plurality of caller identification codes for the caller device, where each of the caller identification codes identifies the caller device in a network; obtaining at least one rule for selecting a caller identification code from the plurality of caller identification codes according to a characteristic of the called device; obtaining a characteristic of the called device; selecting a caller identification code from the plurality of caller identification codes according to the characteristic of the destination telephone identification, or caller environment or destination environment parameters, or caller decision on the time of making the call; and forwarding the selected caller identification code to any of another communication network and a terminal device of a communication network.

A system and method for facilitating communication between an assisted user (AU) and a hearing user (HU) includes receiving an HU voice signal as the AU and HU participate in a call using AU and HU communication devices, transcribing HU voice signal segments into verbatim caption segments, processing each verbatim caption segment to identify an intended communication (IC) intended by the HU upon uttering an associated one of the HU voice signal segments, for at least a portion of the HU voice signal segments (i) using an associated IC to generate an enhanced caption different than the associated verbatim caption, (ii) for each of a first subset of the HU voice signal segments, presenting the verbatim captions via the AU communication device display for consumption, and (iii) for each of a second subset of the HU voice signal segments, presenting enhanced captions via the AU communication device display for consumption.

Systems and methods are provided for dynamic generation of staff analytics and forecasts based on skill and service level. Dynamic forecasting allows for forecast generation in real-time and may be based on historical data regarding skills and results, as well as data science to identify patterns and make predictions. The resulting staffing forecast may therefore provide for efficient management of messaging staff costs while preserving the desired service quality. The staffing forecast may include a volume forecast that is tailored to the unique nature of asynchronous messaging, as well as the unique messaging needs of the entity so as to efficiently manage messaging operations and make data-driven staffing decisions that take service level into account. An exemplary embodiment may include dynamic analytics tools that may use specified target and/or resource numbers (e.g., desired service level) for an existing messaging operation and get a detailed per-skill staffing forecast.

A system and method for adaptive advertisement management for the serving of vehicle description pages and an automated customer engagement thereof. The system is a cloud-based network containing a campaign database, an analytics database, an adaptive advertisement management, a short message service server with automated response capabilities, and user mobile and compute devices that transmit a vehicle description page associated with an advertisement campaign embedded with a communication initiator for display on a customer computing device. Taken together or in part, said system optimizes advertising campaigns across multiple platforms, provides strong analytics for all advertising types while allowing users to engage with advertising quickly and in a real-time automated fashion.

This document relates to creating and/or updating a chatbot using a graphical user interface. For example, training dialogs for a chatbot can be displayed in a tree form on a graphical user interface. Based at least on interactions between a developer and the graphical user interface, the training dialogs can be modified in the tree form, and training dialogs can be updated based on the modifications provided on the tree form via the graphical user interface.

A customer service assistance system includes: storage device that stores an address of an automated response device accumulating knowledge of a provided business in the output screen; and an arithmetic device that, when an inquiry specifying the address is received from a customer terminal, checks identification information of the output screen and an inquiry sentence indicated by the inquiry against questions-and-answers information held for each output screen of the provided business in the automated response device associated with the address, estimates a question matching an intention of the inquiry out of questions in the questions-and-answers information according to whether a screen associated with each question included in the questions-and-answers information matches the output screen and a degree of similarity between a sentence of each question included in the questions-and-answers information and the inquiry sentence, and extracts an answer to the question, and returns the answer to the customer terminal.