Sap Se

Shivendra Kumar Mathur

Ajay Krishna Uniyal

Sampathkumar S

Kalyan Chakravarthy Nannapaneni

Kumar Priyam

Aditya Karanth

Mohd Danish Imam

Leena Khatri

Harish Sivakumaran

Trimurthulu Kondepudi

Systems, methods, and computer-readable media are disclosed for generating uniform hierarchical views of technical documents irrespective of a file format for the technical document. Metadata definitions may be received that define a technical document hierarchy for the technical document. Based on the metadata definitions, technical data element may be mapped to the technical document hierarchy. The technical document may be generated, the technical document comprising the technical data elements. Based in part on the technical document and the metadata definitions, the uniform hierarchical view may be generated. The uniform hierarchical view may be populated with at least a subset of the technical data elements from the technical document. Once generated, the uniform hierarchical view may be displayed.

Uniform hierarchical view over diverse data formats

Provided are a system and method that use machine learning to recommend adjustments to digital documents that are included within a report managed by a software application. The system may also provide a trend analysis as part of the recommendation. In one example, the method may include detecting a request to open a digital document from a user via a user interface, populating the user interface with content from the digital document and executing a machine learning model on values within the digital document to identify a value among the values that is to be adjusted to a different value based on previous adjustments by the user to previous reports, activating a user interface element associated with the identified value within the user interface, and in response to a selection of the user interface element, instantiating a display of the different value on the user interface.

Intelligent adjustment of documents via machine learning

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Bengaluru, India

Shivendra Kumar Mathur