Abstract: A method includes ingesting event data over a network for a plurality of events obtained by disparate computing resources. Each event is associated with a respective timestamp and one or more ingestion-attributes. The method includes identifying whether the corresponding event is associated with any custom indexing-attributes defined by a user. The method also includes indexing the corresponding event into a data store as structured data based on the respective timestamp, the one or more ingestion-attributes, and any identified custom indexing-attributes. The method includes evicting any of the events of the event data in the data store for a period of time that satisfies an eviction time period threshold. The method also includes retrieving the data from the data store that is associated with the time range, the ingestion-attributes, or the one custom indexing-attributes.

Abstract: A method includes ingesting event data over a network for a plurality of events obtained by disparate computing resources. Each event is associated with a respective timestamp and one or more ingestion-attributes. The method includes identifying whether the corresponding event is associated with any custom indexing-attributes defined by a user. The method also includes indexing the corresponding event into a data store as structured data based on the respective timestamp, the one or more ingestion-attributes, and any identified custom indexing-attributes. The method includes evicting any of the events of the event data in the data store for a period of time that satisfies an eviction time period threshold. The method also includes retrieving the data from the data store that is associated with the time range, the ingestion-attributes, or the one custom indexing-attributes.

Abstract: A method includes ingesting event data over a network for a plurality of events obtained by disparate computing resources. Each event is associated with a respective timestamp and one or more ingestion-attributes. The method includes identifying whether the corresponding event is associated with any custom indexing-attributes defined by a user. The method also includes indexing the corresponding event into a data store as structured data based on the respective timestamp, the one or more ingestion-attributes, and any identified custom indexing-attributes. The method includes evicting any of the events of the event data in the data store for a period of time that satisfies an eviction time period threshold. The method also includes retrieving the data from the data store that is associated with the time range, the ingestion-attributes, or the one custom indexing-attributes.

Abstract: A computer-implemented method and an apparatus for automatic execution of at least one next action during a customer interaction receives current information related to a customer from at least one device associated with the customer. At least one next action is determined for the customer in response to the received current information. The at least one next action is determined based on the current information and stored past information corresponding to the customer. Further, an automatic execution of the at least one next action is effected on behalf of the customer if the at least one next action satisfies one or more predefined criteria. The at least one next action is executed on a device from among the at least one device associated with the customer.

Abstract: A computer-implemented method and an apparatus for improving customer interaction experiences determines one or more personas associated with a customer based on customer activity on a plurality of interaction channels. One or more persona profiles corresponding to the one or more personas are generated and maintained, where a persona profile is representative of a set of behavioral traits exhibited substantially consistently by the customer when inhabiting a persona. One or more customer interactions are correlated to at least one persona based on the one or more persona profiles, where the one or more customer interactions are conducted over one or more interaction channels. An intention of the customer is predicted based on the correlation of the one or more customer interactions to the at least one persona.