Abstract: In an embodiment, a method of real-time process monitoring includes initiating monitoring of user interface (UI) activity in a plurality of user environments in which a user-executed process is performed. The user-executed process is defined in a stored instruction set that identifies a plurality of steps of the user-executed process. The plurality of user environments include a first environment operated by a human worker and a second environment operated by a bot. The method also includes, responsive to the initiating, detecting a new process scenario for the user-executed process. The method also includes determining new bot logic for the new process scenario. The method also includes causing the bot to implement the new bot logic.

Abstract: In an embodiment, a method is performed by a computer system and includes intercepting machine learning (ML) input data before the ML input data flows into a ML model. The method also includes scanning the ML input data against a plurality of ML threat signatures, the scanning yielding at least a first result. The method also includes examining a correlation between values of first and second variables in the ML input data, the examining yielding at least a second result. The method also includes validating at least one of the first and second results via a variability analysis of error instances in the ML input data, the validating yielding at least a third result. The method also includes applying thresholding to the ML input data via the third result, where the applying thresholding results in at least a portion of the ML input data being filtered.

Abstract: In an embodiment, a method includes receiving a trigger of machine learning model generation. In addition, the method includes algorithmically eliminating at least some of rows and at least some of columns of a training dataset, the algorithmically eliminating yielding a size-reduced training dataset. The method additionally includes generating, for a prediction target, a plurality of machine learning models via a plurality of machine learning algorithms. The method also includes measuring prediction accuracies of the plurality of machine learning models relative to the prediction target. Furthermore, the method includes selecting a particular machine learning model. Moreover, the method includes applying the particular machine learning model to a data source.

Abstract: In an embodiment, a method includes deploying a learning bot onto a system of bots, where the learning bot monitors a first bot of the system of bots, the first bot executing a first automated process. The method further includes determining a learning phase of the learning bot. The learning bot utilizes a plurality of learning phases including a first learning phase, a second learning phase and a third learning phase. The method also includes, responsive to a determination that the learning bot is in the third learning phase, the learning bot: monitoring activity related to the first automated process; collecting data related to the monitored activity; analyzing at least a portion of the collected data; identifying an automatic tuning adjustment responsive to the analyzing; and automatically making the automatic tuning adjustment to the first automated process.

Abstract: In an embodiment, another general aspect includes a method including, by a compliance bot deployed on a computer system including a system of bots, monitoring the system of bots for deployment activity. The method also includes, responsive to the monitoring, identifying activity indicative of deployment of a particular bot. The method also includes determining an automation type of the particular bot. The method also includes retrieving compliance rules corresponding to the automation type of the particular bot. The method also includes retrieving data from the particular bot. The method also includes automatically checking compliance of the particular bot with the compliance rules based on the retrieved data. The method also includes, responsive to a determination that the particular bot is noncompliant, automatically invalidating the particular bot.