Abstract: A method comprises managing multiple tasks of multiple entities associated with a deployment of a software program with a deployment framework comprising a machine learning module configured to assist with managing the multiple tasks of the multiple entities. The managing step comprises tracking a status of one or more of the multiple tasks, and predicting a time taken for a given one of the multiple entities to complete a given one of the multiple tasks.

Abstract: Methods, apparatus, and processor-readable storage media for augmenting end-to-end transaction visibility using artificial intelligence are provided herein. An example computer-implemented method includes obtaining data related to multiple transaction flows across multiple data sources within an enterprise system, and forecasting anomalies in connection with at least one of the transaction flows by applying one or more of a first set of artificial intelligence techniques to portions of the obtained data, wherein applying the artificial intelligence techniques is based on which of the multiple data sources correspond to the portions of the obtained data. Such a method further includes determining automated actions to be performed in connection with the forecasted anomalies by applying one or more of a second set of artificial intelligence techniques to portions of the obtained data related to the forecasted anomalies, and performing the automated actions in connection with the at least one transaction flow.

Abstract: A method comprises managing multiple tasks of multiple entities associated with a deployment of a software program with a deployment framework comprising a machine learning module configured to assist with managing the multiple tasks of the multiple entities. The managing step comprises tracking a status of one or more of the multiple tasks, and predicting a time taken for a given one of the multiple entities to complete a given one of the multiple tasks.

Abstract: Methods, apparatus, and processor-readable storage media for transaction visibility framework implemented using artificial intelligence are provided herein.

Abstract: The invention relates to an apparatus and a method therewith to quantify visual field in infants. The invention provides a novel solution to the unmet need of detection of defects in the visual field in infants and/or babies and providing an apparatus with a software framework to minimize the errors of recording the readings and increasing their precision and analyzing said results automatically using the software embedded in the system. Said apparatus to quantify visual field in infants comprise of a light projection device onto a dome-shaped hemispherical structure with an infra-red camera along with fixation lights, a means for monitoring responses of the subject during testing, a means for recording and analyzing the readings. Said means to detect and record the eye/head movement in the subject during testing comprises said infra red (IR) camera connected to a device wherein software application is embedded.

Abstract: The invention relates to an apparatus and a method therewith to quantify visual field in infants. The invention provides a novel solution to the unmet need of detection of defects in the visual field in infants and/or babies and providing an apparatus with a software framework to minimize the errors of recording the readings and increasing their precision and analyzing said results automatically using the software embedded in the system. Said apparatus to quantify visual field in infants comprise of a light projection device onto a dome-shaped hemispherical structure with an infra-red camera along with fixation lights, a means for monitoring responses of the subject during testing, a means for recording and analyzing the readings. Said means to detect and record the eye/head movement in the subject during testing comprises said infra red (IR) camera connected to a device wherein software application is embedded.