A user may respond to a request of another user by entering text, such as a customer service representative responding to a customer. As the user enters text, a suggested completion of the text may be suggested to the user so that the user may select the suggested completion instead of continuing to enter text. Previous messages between the two users and other information may be used to determine an appropriate suggested completion to the entered text. A neural network language model and a search graph may be used to select a suggested completion from a search graph of possible suggested completions.

A system or method for dynamic redundant call recording may include a plurality of recording devices, each recording device having a plurality of recording resources, and a resource allocator. The resource allocator may receive a request from a call receiving node for commencement of a recording session. It may then attempt to connect to a first one of the plurality of recording devices and if successful, establish a recording session between the call receiving node and the recording device, or if not successful, attempting to connect the recording session controller to a second one of the multiple recording devices. Two resource allocators may operate in parallel to establish dual recording using resources at two different recording devices. Call content may be recorded separately from call metadata and may be integrated with the metadata using a unique call ID.

Agent conversation item selection is automated by a server that automatically detects speech in a call and converts that speech to text. Software running on the server retrieves one or more items from a data store based on a determination that the text includes one or more keywords or a change in the subject of the call. The keywords can include phrases. The retrieved items include one or more of scripts, articles, manuals, daily bulletins regarding a system state, or any resource that can be used to assist with a customer call or interaction. The software running on the server generates a user interface (UI) output based on the retrieve items, and transmits the UI output to an agent device. Software running on the agent device receives the UI output and displays the retrieved items on a display of the agent device.

A system and method for intent-based active callback management using enhanced callback objects, utilizing a cloud callback system comprising at least a profile manager, callback manager, interaction manager, media server, and environment analyzer, allowing users to call businesses, agents in contact centers, or other users who are connected to a cloud callback system, and, failing to connect to the individual they called, allow for an automatic callback object to be created, whereby the two users may be automatically called and bridged together at a time when both users are available.

A mobile application for a wireless handheld computing device, such as a smartphone, is disclosed in combination with a communication link establishment and management system. Systems and methods are disclosed for calling desired contacts using a smartphone that can take advantage of the power and efficiency of agent-assisted dialing provided by the communication link establishment and management system. The systems and methods automatically integrate with a customer relationship management (CRM) system connected to the communication link establishment and management system.

A system for generating a merged agent log starts with a processor receiving an audio signal of a communication session between a member-related client device and an agent client device. Processor processes the audio signal to generate caller utterances and generates identified tasks based on the caller utterances. The processor then generates caller utterance data including the identified tasks and a start time of the caller utterances and an end time of the caller utterances. The processor groups the caller utterances based on the identified tasks, and for each of the identified tasks, the processor generates an agent log using an agent logging neural network. The agent log is based on the caller utterances. Other embodiments are disclosed herein.

An on-premises system for pre-processing data for forecasting according to an embodiment includes at least one processor and at least one memory having a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the on-premises system to receive a request to forecast contact center data using a cloud system, determine a first number of interactions per unit of time for a source interval, determine a second number of units of time in a destination interval, and determine a third number of interactions in the destination interval based on the first number of interactions per unit of time for the source interval and the second number of units of time in the destination interval.

A computerized-method using a cloud-based computing environment for improving client service, in a contact center is provided herein. The computerized-method includes: retrieving a context of a query and a time-limit from a CTI event and attempting to retrieve data to evaluate average resolution time for the received context. When the data is found, comparing the evaluated average resolution time with the received time-limit and when the received time-limit is below the evaluated average resolution time, sending a delay notice and providing the client a menu of options for querying through other channels. When the data is not found, or when the received time-limit is above the evaluated average resolution time, presenting on an agent dashboard, the time-limit of the client and accordingly updating parameters in the agent dashboard during the inbound call, thus, improving client service, by considering the time-limit of the client before the agent addresses a query.

A system for utilizing conversational artificial intelligence (AI) to train contact center agents according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored therein that, in response to execution by the at least one processor, causes the system to place a virtual call from an automated training system to an agent device of an agent, connect the virtual call to a chatbot in response to establishing a communication connection with the agent device, transmit one or more statements from the chatbot, receive, from the agent device, one or more agent responses of the agent corresponding to the one or more statements, and analyze the one or more agent responses to determine one or more training characteristics associated with AI-based contact center training of the agent.

A system and method for unified autodial campaign management, comprising a campaign management console, a data services engine, a traffic shaper, an agent desktop, Control agent desktop, an auto-dialer, and a simple dialer which allows enterprises to conduct unified communications campaigns without differentiating between prior expressed written consent consumers, and those who have not provided prior expressed written consent, to being autodialed or receiving artificial or pre-recorded voice messages, allowing for compliance with regulations regarding such consent without splitting or bifurcating or otherwise hampering communications campaigns for the enterprise customers.