US-20260129125-A1 - Computer Architecture For Intelligent Agent Escalation In A Contact Center

US20260129125A1US 20260129125 A1US20260129125 A1US 20260129125A1US-20260129125-A1

Abstract

A contact center server obtains, during a contact center engagement, a response to a user prompt received from a user device. The response comprises natural language data and a workflow. The contact center server determines, based on activity of the user device associated with the workflow, to connect the user device to an agent device. The agent device is different from a device that generated the natural language data and the workflow. The contact center server generates, using a transformer engine, a summary of the contact center engagement. The summary is a summarization of the natural language data and a representation of user interaction with the workflow. The contact center server transmits, in response to determining to connect the user device to the agent device, the summary for display at the agent device in conjunction with a request for the agent device to connect to the contact center engagement.

Inventors

David Robert DeLorimier
Maikl Adly Abdel-Malek Eskander
Tetsumasa Yoshikawa

Assignees

ZOOM COMMUNICATIONS, INC.

Dates

Publication Date: 20260507
Application Date: 20241107

Claims (20)

1 . A method, comprising: obtaining, by a contact center server during a contact center engagement, a response to a user prompt received from a user device, the response comprising natural language data and a workflow; determining, by the contact center server and based on activity of the user device associated with the workflow, to connect the user device to an agent device; generating, using a transformer engine of the contact center server, a summary of the contact center engagement, the summary comprising a summarization of the natural language data and a representation of user interaction with the workflow; and transmitting, by the contact center server in response to determining to connect the user device to the agent device, the summary for display at the agent device in conjunction with a request for the agent device to connect to the contact center engagement.
2 . The method of claim 1 , wherein the agent device is different from a device that generated the response.
3 . The method of claim 1 , further comprising: tracking, by the contact center server, the activity of the user device associated with the workflow.
4 . The method of claim 1 , wherein obtaining the response comprises: obtaining, by the contact center server, the response from an initial agent device different from the agent device.
5 . The method of claim 1 , wherein obtaining the response comprises: obtaining the response from a virtual agent engine of the contact center server.
6 . The method of claim 1 , wherein the natural language data comprises at least one of text or speech.
7 . The method of claim 1 , wherein determining to connect the user device to the agent device comprises: determining, by the contact center server, to connect the user device to the agent device based on at least one of a request from the user device or a determination, by the contact center server, to connect to the agent device.
8 . The method of claim 1 , wherein the summarization of the natural language data comprises a natural language text summary, wherein the representation of the user interaction with the workflow comprises a graphical representation of user progress through the workflow, the method further comprising: generating, by the contact center server, the graphical representation using the transformer engine and based on a specified format for the graphical representation.
9 . The method of claim 1 , wherein the workflow comprises a knowledgebase article, wherein the representation of the user interaction with the workflow comprises an indication of whether the user device viewed the knowledgebase article.
10 . The method of claim 1 , wherein the workflow comprises a knowledgebase article, wherein the representation of the user interaction with the workflow comprises an indication of scrolling through the knowledgebase article and an indication of positions in the knowledgebase article where the scrolling was paused.
11 . The method of claim 1 , further comprising training the transformer engine by: pretraining the transformer engine on a corpus of at least one of text, audio, or video in a pretraining phase; and finetuning the transformer engine to generate summaries of contact center engagements based on recorded videos of contact center engagements available on video hosting web services.
12 . The method of claim 1 , further comprising: determining, by the contact center server and based on data associated with communication between the user device and the agent device, that the workflow was correctly presented in response to the user prompt; determining, using the transformer engine, a reason why the user device did not complete the workflow prior to connection of the agent device; and revising, by the transformer engine, the workflow based on the reason.
13 . The method of claim 1 , wherein the contact center server comprises a server farm including multiple machines.
14 . A non-transitory computer readable medium storing instructions operable to cause one or more processors to perform operations comprising: obtaining, by a contact center server during a contact center engagement, a response to a user prompt received from a user device, the response comprising natural language data and a workflow; determining, by the contact center server and based on activity of the user device associated with the workflow, to connect the user device to an agent device; generating, using a transformer engine of the contact center server, a summary of the contact center engagement, the summary comprising a summarization of the natural language data and a representation of user interaction with the workflow; and transmitting, by the contact center server in response to determining to connect the user device to the agent device, the summary for display at the agent device in conjunction with a request for the agent device to connect to the contact center engagement.
15 . The non-transitory computer readable medium of claim 14 , the operations further comprising: tracking, by the contact center server, the activity of the user device during the contact center engagement.
16 . The non-transitory computer readable medium of claim 14 , wherein obtaining the response comprises: obtaining, by the contact center server, the response from at least one of an initial agent device different from the agent device or a virtual agent engine of the contact center server.
17 . The non-transitory computer readable medium of claim 14 , wherein the natural language data comprises at least one of natural language text or natural language speech.
18 . The non-transitory computer readable medium of claim 14 , wherein determining to connect the user device to the agent device comprises: determining, by the contact center server, to connect the user device to the agent device based on a request from the user device.
19 . A system, comprising: a memory subsystem storing instructions; and processing circuitry configured to execute the instructions to: obtain, by a contact center server during a contact center engagement, a response to a user prompt received from a user device, the response comprising natural language data and a workflow; determine, by the contact center server and based on activity of the user device associated with the workflow, to connect the user device to an agent device; generate, using a transformer engine of the contact center server, a summary of the contact center engagement, the summary comprising a summarization of the natural language data and a representation of user interaction with the workflow; and transmit, by the contact center server in response to determining to connect the user device to the agent device, the summary for display at the agent device in conjunction with a request for the agent device to connect to the contact center engagement.
20 . The system of claim 19 , wherein the workflow comprises an article, wherein the representation of the user interaction with the workflow comprises an indication of positions in the article where scrolling through the article was paused.

Description

FIELD This disclosure generally relates to artificial intelligence in contact centers, and, more specifically, to the use of artificial intelligence in adding an agent to a contact center engagement. BRIEF DESCRIPTION OF THE DRAWINGS This disclosure is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. FIG. 1 is a block diagram of an example of an electronic computing and communications system. FIG. 2 is a block diagram of an example internal configuration of a computing device of an electronic computing and communications system. FIG. 3 is a block diagram of an example of a software platform implemented by an electronic computing and communications system. FIG. 4 is a block diagram of an example of a contact center system. FIG. 5 is a block diagram of an example of a system for intelligent agent escalation. FIG. 6 is a data flow diagram of an example of intelligent agent escalation. FIG. 7 is a block diagram of phases of training a generative pretrained transformer (GPT). FIG. 8 illustrates a first example of a graphical user interface (GUI) for user communication with a contact center server. FIG. 9 illustrates a second example of a GUI for user communication with a contact center server. FIG. 10 illustrates a third example of a GUI for user communication with a contact center server. FIG. 11 illustrates an example of a GUI for inviting an agent to join a contact center engagement. FIG. 12 is a flowchart of an example of a technique for intelligent agent escalation. FIG. 13 is a flowchart of an example of a technique for identifying a workflow for revision. DETAILED DESCRIPTION The use of contact centers by or for service providers is becoming increasingly common to address customer support requests over various modalities, including telephony, video, text messaging, chat, and social media. In one example, a contact center may be implemented by an operator of a software platform, such as a unified communications as a service (UCaaS) platform or a contact center as a service (CCaaS) platform, for a customer of the operator. Users of the customer may engage with the contact center to address support requests over one or more communication modalities enabled for use with the contact center by the software platform. In another example, the operator of such a software platform may implement a contact center to address customer support requests related to the software platform itself. During a contact center engagement, a user of a user device may in some cases initially be connected with a virtual agent engine of a contact center. The user may provide a user prompt stating the reason for the contact center engagement, and the virtual agent engine may provide a natural language response, as well as a workflow (e.g., a set of steps to take or a knowledgebase article to read) for responding to the user prompt. In some cases, the user might desire to continue the contact center engagement with a human agent, or the contact center server may otherwise determine that a human agent would be more effective at addressing the user prompt. In such circumstances, an agent device of the human agent may be added to the contact center engagement and may be provided with the user prompt. In response, the human agent, via their agent device, might generate a similar natural language response or propose the same workflow as the virtual agent engine, frustrating the user and decreasing the goodwill of the user to an organization associated with the contact center. As the foregoing illustrates, techniques for avoiding the repetition of natural language responses and workflows during contact center engagements may be desirable. Furthermore, informing the human agent of what has already transpired in the contact center engagement may be desirable to allow the human agent to most effectively assist the user, for example, by determining where the user experienced difficulties in performing the workflow or interacting with the virtual agent. Implementations of this disclosure address problems such as those described above by using a transformer engine to summarize a contact center engagement to a human agent when the agent device of the human agent is added to the contact center engagement. During the contact center engagement, a contact center server facilitating the contact center engagement receives a user prompt from a user device. The contact center server generates, using a virtual agent engine, a response to the user prompt. The response includes natural language data (e.g., text or speech) and a workflow (e.g., a knowledgebase article or a set of steps to complete). The contact center server determines that the user device is to be connected to the agent de