Abstract: A computer-implemented method for identifying a potential system-wide failure in a computerized system is provided. The method includes receiving a plurality of tickets generated by users of the computerized system, wherein at least some of the tickets include data pertaining to system failures, classifying, based on the data, at least some of the tickets to respective one or more classification categories included in a hierarchical failure classification data structure comprising a plurality of classification categories, wherein each of the categories is associated with a system failure, wherein the data structure was generated using machine learning techniques applied to historical ticketing information including a plurality of historical tickets and corresponding system failures, monitoring the one or more categories to identify a potential system-wide failure; and in response to identifying a potential system-wide failure, performing an action.

Abstract: A system and a method of automatically allocating by an autonomous orchestration of work items to organizational resource are provided herein. The method may include the following steps: obtaining a stream of work items allocation requests from a delivery management system; analyzing the stream of work items allocation requests, to extract work items specification from the requests; applying an optimization of the human resources vis a vis the work items specifications; and providing recommendation for allocation of said work items to the delivery management system.

Abstract: A computer implemented method for generating a performance rating for a developer may include monitoring developer activities to obtain near real-time activity data; exploring the near real-time activity data to identify entities; structuring the near real-time activity data into data-frame objects; performing a feature engineering procedure to measure representative behaviors of the developer and performing a performance analysis to produce performance rating of the developer.

Abstract: A computer implemented method for generating a performance rating for a developer may include monitoring developer activities to obtain near real-time activity data; exploring the near real-time activity data to identify entities; structuring the near real-time activity data into data-frame objects; performing a feature engineering procedure to measure representative behaviors of the developer and performing a performance analysis to produce performance rating of the developer.