Dell Products Inc.

Emc IP Holding Company LLC

Rishav Sethia

Vivek Bhargava

Vaideeswaran Ganesan

Abhishek Mishra

Shubham Gupta

Ajith Navada

An apparatus comprises a processing device configured to obtain messages associated with actions taken in applications running on at least one information technology asset in an information technology infrastructure, and to parse the messages to create message records, a given message record associated with a given message identifying actions taken in a given one of the applications, entities for which the actions in the given application were performed, and topics that the given message is associated with. The processing device is also configured to determine cross-application dependencies between the actions based at least in part on correlating entities and topics across the message records, a given cross-application dependency characterizing a relationship between first and second actions taken in first and second ones of the applications. The processing device is further configured to control performance of subsequent actions in the applications based at least in part on the determined cross-application dependencies.

Message parsing to determine cross-application dependencies among actions from different applications

Methods, apparatus, and processor-readable storage media for automatically determining and implementing messaging characteristics using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining one or more context-based messaging characteristics for at least one user device based on message-related data associated with the user device(s) and one or more software applications running on the user device(s); prioritizing at least one of multiple messages intended for the user device(s) by processing the messages, in connection with at least a portion of the context-based messaging characteristic(s), using a first set of artificial intelligence techniques; determining one or more temporal values associated with transmitting the prioritized message(s) to the user device(s) by processing the messages, in connection with the context-based messaging characteristic(s), using a second set of artificial intelligence techniques; and automatically transmitting the prioritized message(s) to the user device(s) in accordance with the temporal value(s).

Automatically determining and implementing messaging characteristics using artificial intelligence techniques

Methods, apparatus, and processor-readable storage media for converting text data to video data using artificial intelligence techniques are provided herein. An example computer-implemented method includes converting text data associated with a task into multiple action statements relating to user performance of at least a portion of the task; generating video data by processing at least a portion of the multiple action statements using one or more artificial intelligence techniques; compiling at least a portion of the generated video data into at least one video sequence corresponding to at least one action workflow for the user performance of the at least a portion of the task; and performing one or more automated actions based at least in part on the at least one video sequence.

Converting text data to video data using artificial intelligence techniques

An apparatus comprises a processing device configured to receive and parse a search request related to a given event to identify confident terms, and to determine a first subset of the confident terms which indirectly reference the given event and a second subset of the confident terms which are not in the first subset. The processing device is also configured to identify, for a given confident term in the second subset, terms having at least a threshold level of semantic similarity with the given confident term, and to construct a primary search query comprising the first and second subsets of the confident terms and additional search queries comprising the first subset of the confident terms and the identified one or more terms having at least the threshold level of semantic similarity with the given confident term. The processing device is further configured to execute the primary and additional search queries.

Constructing and executing search queries with terms semantically similar to those of a search request

An apparatus comprises a processing device configured to obtain one or more messages, the one or more messages being associated with management of a given one of one or more information technology assets in an information technology infrastructure, and to determine, based at least in part on content of a given one of the one or more messages, whether the given message is suitable for delivery in an audio format. The processing device is also configured, responsive to determining that the given message is suitable for delivery in the audio format, to convert the content of the given message into one or more audio messages. The processing device is further configured to select one or more audio output devices for delivery of the one or more audio messages, and to provide, to the selected one or more audio output devices, the one or more audio messages.

Conversion of messages into audio format

Methods, apparatus, and processor-readable storage media for automatically validating design parameters for enterprise applications are provided herein. An example computer-implemented method includes obtaining image data and code data of a given application associated with an enterprise; processing at least a portion of the image data against at least a portion of design parameters of the enterprise by processing the at least a portion of the image data and a set of design-compliant image data using similarity algorithms; processing at least a portion of the code data against at least a portion of the design parameters by performing an automated scan of the at least a portion of the code data against at least one code-related portion of the design parameters; and performing automated actions based on the processing of the image data and/or the processing of the code data.

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Bengaluru, India

Rishav Sethia