Servicenow, Inc.

Scott Michael Rhodes

Prithvi Yoganand

Victor Chung-Wai Chan

Gaurav Goyal

Harish Kumar Balachandra Bellamane

Surabhi Seetharam

Daniel Li-Shuan Wu

Yong Liang

Vani Banaji

Balaji Cuttackam

Adam Wesley Moguel

Chinmayee Nagaraju

Evan Ross Lipton

Samantha Santo

Alisson Douglas Da Silveira Pacheco

Parul Upadhyaya

Arun Shivaramakrishna

Srikanth Mallikarjuna

Andrew Thomas Roberts

Ruoyu Wang

Tian Ye

Stephen Witmer

Vinay Mohan

Ravi Ambati

Kristopfer P Krueger

Philip Casini

Nidhi Srinivas

An indication from a live agent in a communication session with a user to invoke a specified automated agent interactive conversation flow is received. The communication session with the user is transitioned from the live agent to the specified automated agent interactive conversation flow. During the specified automated agent interactive conversation flow, the live agent retains control over the communication session. An indication of an interaction of the user with the specified automated agent interactive conversation flow is provided. The communication session with the user is returned back to the live agent.

Invokable automated agent for interactive workflows

Persistent storage contains a state machine for a request routing process and a plurality of requests related to the request routing process. One or more processors are configured to apply the state machine through operations including: obtaining a request from the plurality of requests; providing, to a criticality detection application and to an intent detection application, a representation of the request, wherein the criticality detection application is configured to detect a criticality of the request, and wherein the intent detection application is configured to determine a semantic intent of the request; receiving, from the criticality detection application and the intent detection application, respective indications of a detected criticality of the request and a detected intent of the request; determining whether to route the request to a channel that is one of a live agent, a virtual agent, or a search-based application; and routing the request to the channel as determined.

Hybrid request routing system

In accordance with the present approach, a collaborative chat system is provided that enables collaborative communication between a user preferring a native chat platform and a different user who communicates using a non-native or third-party chat platform. The user may particularly select various other users to be added to a collaborative chat, regardless of which chat platform the other users have set as their main or preferred communication channel. Indeed, when displaying the various users available to be added to the collaborative chat, the collaborative chat system may display a visual indication or icon that indicates which chat platform the various users are available through. The collaborative chat system or platform may utilize bi-directional communications between the native chat platform and any communicatively coupled third-party chat platforms to link the user with the selected other users within a collaborative chat instance.

Systems and methods for collaborative chat with non-native chat platforms

An example system for dynamic agent management involving multiple queues is presented. The system may include a remote network management platform that manages a network by way of a computational instance. A first group and a second group of agents may be assigned to address work items in a first queue in the computational instance. The second group may also be assigned to address and prioritize work items in a second queue in the computational instance. A computing device within the computational instance may assign a work item originating from a client device in the managed network into the first queue according to routing rules. The assignment may cause a timer to record a duration that the work item is in the first queue. The computing device may assign one of the second group of agents to address the work item based on the duration exceeding a pre-determined value.

Dynamic agent management for multiple queues

A computational instance may contain queues configured to hold work items. The work items may be representations of user submissions requesting actions from a plurality of agents. The computational instance may also contain computing devices configured to: (a) obtain a set of assignment rules that specify mappings between (i) respective selection criteria for the assignment rules, and (ii) one or more candidate agents from the plurality of agents that can be assigned to address the work items with content that match the respective selection criteria, (b) read, from the queues, a work item corresponding to a user submission, (c) iterate through the assignment rules according to an ordering until a particular assignment rule with associated selection criteria that matches content of the work item is found, and (d) assign the work item to a particular agent from the one or more candidate agents.

Workflows with rule-based assignments

An embodiment may involve persistent storage containing definitions of a set of queues and a set of servers, and wherein the servers are respectively associated with deactivation times. One or more processors may be configured to: (i) identify, by an assignment engine, an incoming request in a particular queue, wherein the incoming request is ready for assignment to one of the servers; (ii) determine, by the assignment engine and based on data associated with the incoming request, an expected duration for servicing of the incoming request; (iii) calculate, by the assignment engine and based on the deactivation times, times remaining in service for each of the servers; (iv) select, by the assignment engine and from the servers, a particular server that has a time remaining that is greater than the expected duration; and (v) assign, by the assignment engine, the incoming request to the particular server.

Assignments of incoming requests to servers in computing clusters and other environments

Utilizing quick actions includes receiving user input via a user input module of an agent workspace, wherein the user input comprises an action input comprising an action command, and in response to receiving the user input, determining a secondary menu for the action command, wherein the secondary menu comprises a plurality of selectable parameters for the action command, and presenting the secondary menu in association with the user input module. Utilizing quick actions also includes detecting a selection of a parameter from the selectable parameters, and triggering an action based on the action command and the selected parameter, wherein the action is associated with a process for the agent workspace.

Quick actions

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Torrance, CA, United States of America

Scott Michael Rhodes