Abstract: Disclosed is system for enabling generation of industry-tailored virtual assistants. System comprises server(s) and data repository communicably coupled to server(s), wherein server(s) is configured to: receive raw conversation data from at least one data source, transform raw conversation data to generate processed conversation data, generate taxonomy(-ies) of industry using processed conversation data, label processed conversation data to generate labelled conversation data, create relationships between entities in labelled conversation data and taxonomy(-ies), generate dataset pertaining to digital warehouse that is usable to generate industry-tailored virtual assistants, and provide digital warehouse using dataset on digital portal that is accessible by target device(s) wherein digital portal is hosted by server(s), wherein digital warehouse comprises listings for set of items including one or more of: intent(s), skill(s), virtual assistant template(s), pre-built and pre-trained virtual assistant(s).

Abstract: Disclosed is a method comprising receiving user query (UQ) indicative of task (202) associated with retrieval of data (204) from database (206) comprising structured and unstructured data sources (SAUDS) (208) and generating relevant response (RR) (210) for UQ; generating task plan (220) for determining embedding (224) for task, performing retrieval task (226) for identifying relevant SAUDS (228), generating relevance scores (230), and when relevance scores indicate unstructured pipeline (232): triggering unstructured data query engine (UDQE) (234, 306) for retrieving data, and generating RR, or when relevance scores indicate structured pipeline (236): triggering structured data query engine (SDQE) (238, 308) for retrieving data, and generating RR, or when relevance scores indicate hybrid pipeline (240): triggering SDQE for retrieving first portion of data (FPD) (242), transforming received UQ and FPD, triggering UDQE for retrieving second portion of data (SPD) (246), and combining FPD and SPD for generating

Abstract: Disclosed is a system and a method for semantic search in an enterprise. The method comprises defining entities in the enterprise, indexing content from one or more data sources of the enterprise to determine relationships between individual pieces of the content and one or more of the entities, providing an interface to allow a user to enter a search query, parsing the search query, determining relevant pieces of the content based on the parsed search query, identifying the one or more of the entities for each of the relevant pieces of content based on the relationships therebetween and configuring the interface to display each of the relevant pieces of the content under respective one or more of the entities in response to the search query.

Abstract: Disclosed is a system and method for managing user interactions with a client device. The method comprises receiving from a telecommunication network, connected to the client device, a session request; processing the session request to determine relay information for routing the session request; transmitting the session request to a trained virtual agent based on the relay information, wherein the trained virtual agent is configured to process the session request to generate a command signal; and transmitting the command signal, via a private exchange mechanism, to the client device to establish the session for user interaction, wherein the data transmission between the client device and the trained virtual agent is based on a predefined protocol.

Abstract: Disclosed is a system and a method for semantic search in an enterprise. The method comprises defining entities in the enterprise, indexing content from one or more data sources of the enterprise to determine relationships between individual pieces of the content and one or more of the entities, providing an interface to allow a user to enter a search query, parsing the search query, determining relevant pieces of the content based on the parsed search query, identifying the one or more of the entities for each of the relevant pieces of content based on the relationships therebetween and configuring the interface to display each of the relevant pieces of the content under respective one or more of the entities in response to the search query.

Abstract: Disclosed is a system and method for managing user interactions with a client device. The method comprises receiving from a telecommunication network, connected to the client device, a session request; processing the session request to determine relay information for routing the session request; transmitting the session request to a trained virtual agent based on the relay information, wherein the trained virtual agent is configured to process the session request to generate a command signal; and transmitting the command signal, via a private exchange mechanism, to the client device to establish the session for user interaction, wherein the data transmission between the client device and the trained virtual agent is based on a predefined protocol.

Abstract: Disclosed is system for enabling generation of industry-tailored virtual assistants. System comprises server(s) and data repository communicably coupled to server(s), wherein server(s) is configured to: receive raw conversation data from at least one data source, transform raw conversation data to generate processed conversation data, generate taxonomy(-ies) of industry using processed conversation data, label processed conversation data to generate labelled conversation data, create relationships between entities in labelled conversation data and taxonomy(-ies), generate dataset pertaining to digital warehouse that is usable to generate industry-tailored virtual assistants, and provide digital warehouse using dataset on digital portal that is accessible by target device(s) wherein digital portal is hosted by server(s), wherein digital warehouse comprises listings for set of items including one or more of: intent(s), skill(s), virtual assistant template(s), pre-built and pre-trained virtual assistant(s).

Abstract: A method and system for generating a response through a virtual agent is provided herein. The method comprises receiving information associated with a plurality of themes and topics. The method further comprises creating a knowledgebase based on the information received. The method further comprises analyzing the knowledgebase based on an intent identified, using an Artificial Intelligence (AI) model. Further, the method comprises generating a response corresponding to the intent through the virtual agent based on analyzation.

Abstract: A method and system for generating conversation flows is provided herein. The method and system comprise storing conversations between at least an agent and at least a user in logs. Further, the method and system comprise extracting topics from the logs. Also, the method and system comprise creating clusters from the extracted topics. The method and system further comprise generating the conversation flows from the clusters.

Abstract: A method and system for training a virtual agent through fallback analysis is provided herein. The method comprises obtaining a plurality of fallback utterances. The method further comprises classifying the plurality of fallback utterances into one or more of existing intent categories, via a Machine Learning (ML) model. The method further comprises upon unsuccessful classification of one or more utterances of the plurality of fallback utterances, clustering the one or more utterances into one or more groups based on similarities among the one or more utterances, via the ML model. Further, the method comprises generating labels for the one or more groups to determine names of new intent categories associated with the one or more utterances.

Abstract: A method and system for training a virtual agent is provided herein. The method and system comprises storing conversations between the virtual agent and a user in logs. The method and system further comprises mining the logs to retrieve utterances. The method and system further comprises computing regression for each of the plurality of the charging time segments. The method and system further comprises providing a score to the utterances. Further, the method ranking the utterances based on the score.