Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the Ll IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: A multi-domain chatbot is used to service a message of a user. An automated agent of the multi-domain chatbot may act as an intermediary between the user and a plurality of domain-specific modules of the multi-domain chatbot. The automated agent may receive the message from the user, determine an intent of the message, and based on the intent, determine a group of the domain-specific modules that should be investigated. The automated agent may then investigate the group of domain-specific modules by sending the user message to and receiving responses from the domain-specific modules within the group. Based on the received responses, the automated agent may determine whether to provide, to the user, one of the domain-specific responses or a null response, in the event that none of the domain-specific responses is aligned with the intent of the message.

Abstract: An automated service agent may be used to service issues discussed by users of a group communication channel. In the process of servicing the issue, the automated service agent may differentiate the roles of the users and identify a requester of the issue. In one scenario, the automated service agent may contact the requester in a private communication channel to collect more detailed or private information from the requester. The issue may be resolved in the private communication channel with the requester. Information may be posted back to the group communication channel to inform the other users as to the successful resolution of the issue and how the issue was resolved. While communicating with the requester in the private communication channel, messages may be posted to the group communication channel to keep the other users up to date on the progress of resolving the issue in the private communication channel.

Abstract: An automated agent may communicate with a user via a chat channel to proactively alert the user of an L1 IT support issue. The L1 IT support issue may be determined based on monitoring indications of human-initiated activities maintained by a system of record, and may, prior to the automated agent's alert, be unknown to the user. In some instances, a natural language understanding (NLU) module may be used to identify an entity and intent from the indications of human-initiated activities, and the L1 IT support issue may be determined based on the determined entity and intent. After alerting the user of the L1 IT support issue, the automated agent may inform, via the chat channel, the user of a remediation step available to address the L1 IT support issue. Upon obtaining the user's permission, the automated agent may perform the remediation step to address the L1 IT support issue.

Abstract: A multi-domain chatbot is used to service a message of a user. An automated agent of the multi-domain chatbot may act as an intermediary between the user and a plurality of domain-specific modules of the multi-domain chatbot. The automated agent may receive the message from the user, determine an intent of the message, and based on the intent, determine a group of the domain-specific modules that should be investigated. The automated agent may then investigate the group of domain-specific modules by sending the user message to and receiving responses from the domain-specific modules within the group. Based on the received responses, the automated agent may determine whether to provide, to the user, one of the domain-specific responses or a null response, in the event that none of the domain-specific responses is aligned with the intent of the message.

Abstract: A computer-implemented method for conducting a conversation with a virtual agent system is provided. The method includes receiving a conversation input from a user during a conversation of the user with a virtual agent system. The method includes probabilistically matching the conversation input with a stack of earlier conversations between the user and the virtual agent system. The probabilistic matching determines a context of the conversation input from one or more contexts associated with the stack of earlier conversations. The method includes interpreting the conversation input to identify a user intent from among a plurality of user intents. The method further includes determining an action to be performed by the virtual agent system based on the context determined by the probabilistic matching and the user intent.

Abstract: Method, system and computer program product for facilitating query resolution at a service desk associated with an enterprise are disclosed. A user interface (UI) is provisioned to a user to enable the user to provide a query to a virtual agent. The virtual agent engages in an interaction with the user to determine whether the query is a service request or an incident. If the query is determined to be a service request, then a service request form is updated based on the interaction. The updated service request form is routed to a resolver queue identified to be relevant to the service request. If the query is determined to be an incident, then a reply to the query is identified from a knowledge base and the reply is provisioned to the user using the UI.

Abstract: Method, system and computer program product for facilitating task automation at an IT service desk associated with an enterprise are disclosed. A user interface (UI) is provisioned to a user to enable the user to provide a request in a natural language form to the IT service desk. A virtual agent engages in a natural language interaction with the user on the UI and interprets the request from the natural language interaction. The request is mapped to a set of pre-determined actions based on the interpretation of the request and an execution of the set of pre-determined actions is effected to facilitate resolution of the request provided by the user.

Abstract: A server has a data processing module with instructions executed by a processor to maintain an annotation of a first visualization of data, where the first visualization of data has visualization configuration parameters. The annotation is linked to a second visualization of the data that utilizes the visualization configuration parameters.

Abstract: A server includes a data ingestion module with executable instructions executed by a processor to produce inferred data types from received data and utilize the inferred data types to augment the received data with computed values that aggregate the received data along a hierarchical dimension.

Abstract: A server includes a data processing module with executable instructions executed by a processor to produce a first inferred data type from first received data and a second inferred data type from second received data. The first inferred data type is utilized to augment the first received data with computed values that aggregate the first received data along a first hierarchical dimension. The second inferred data type is utilized to augment the second received data with computed values that aggregate the second received data along a second hierarchical dimension. The first hierarchical dimension and the second hierarchical dimension are harmonized to a lowest common unit value. A first visualization of the first received data is provided based upon the lowest common unit value. A second visualization of the second received data is provided based upon the lowest common unit value.

Abstract: A server includes a data ingestion module with executable instructions executed by a processor to produce inferred data types from received data and utilize the inferred data types to augment the received data with computed values that aggregate the received data along a hierarchical dimension.

Abstract: A computer system includes a firewall between the computer system and an external network. Private data sources are protected by the firewall. An agent executed behind the firewall is configured to connect to a target data repository external to the firewall, specify a data set in the form of a query against one or more of the private data sources, generate the data set by executing the query against one or more of the private data sources, and export the data set through the firewall and into the target data repository.

Abstract: A server has a data processing module with instructions executed by a processor to maintain a collection of data units, where the collection of data units includes data from multiple data sources. A collection of discussion threads is maintained. Each discussion thread is associated with a data unit and each discussion thread uniquely identifies different users and comments made by the different users.

Abstract: A server includes a data processing module with executable instructions executed by a processor to produce a first inferred data type from first received data and a second inferred data type from second received data. The first inferred data type is utilized to augment the first received data with computed values that aggregate the first received data along a first hierarchical dimension. The second inferred data type is utilized to augment the second received data with computed values that aggregate the second received data along a second hierarchical dimension. The first hierarchical dimension and the second hierarchical dimension are harmonized to a lowest common unit value. A first visualization of the first received data is provided based upon the lowest common unit value. A second visualization of the second received data is provided based upon the lowest common unit value.

Abstract: A server has a data processing module with instructions executed by a processor to maintain an annotation of a first visualization of data, where the first visualization of data has visualization configuration parameters. The annotation is linked to a second visualization of the data that utilizes the visualization configuration parameters.

Abstract: An updateable list is provided for use in mounting a storage volume. Such list may include a plurality of block references capable of being used to access corresponding blocks required for mounting the storage volume. In use, such list may be utilized for accessing the blocks in a more efficient manner, by accessing a plurality of such blocks in parallel, as well as performing the block accessing and storage volume mounting in parallel.