A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: selecting an organizational value from a plurality of organizational values, at least one of the plurality of organizational values representing a value associated with an information technology (IT) environment; analyzing organizational value goals associated with the IT environment, the analyzing comprising at least one of prioritizing and weighting the organizational value goals; generating a recommendation based upon the analyzing; and, presenting the recommendation via a project recommendation user interface.

Systems and methods to provide actionable insights to online environment providers based on an online environment and psychological attributes of users are disclosed. Exemplary implementations may: obtain cluster information for individual clusters; obtain environment information characterizing an online environment of the individual clusters; obtain performance information that characterizes performances of user behavior patterns within the online environment by the users of individual ones of the subclusters; determine response actions for implementation by a provider server of the online environment based on the individual subclusters, the performance information, and the environment information; and transmit the response actions to the provider server for implementation.

An automated, multi-stage decommissioning method for business intelligence artifacts may comprise generating a classification for a business intelligence artifact in a business intelligence environment; determining, based on the classification, whether the business intelligence artifact is a target artifact to be decommissioned; and if the business intelligence artifact is determined to be a target artifact, then initiating a decommissioning process on the target artifact.

A method for producing a well includes receiving production information associated with wells within a field; deriving a field specific model from the production information; receiving production information associated with the well; projecting production changes associated with installing artificial lift at the well at a projected date, the projecting using a production analysis engine applied to the field specific model, the projecting including determining a set of artificial lift parameters; and installing the artificial lift at the well in accordance with the artificial lift parameters.

Store a subscription dataset for each tenant of a multi-tenant system, each of the subscription datasets having a common data format native to the system, the subscription datasets including billing data and not behavioral data. Determine primary features from a particular subscription dataset. Derive secondary features from the primary features. Generate a churn prediction model based on the primary features and the secondary features. Obtain a second subscription dataset, the second subscription dataset comprising billing data that is more recent than the particular subscription dataset. Identify, using the particular churn prediction model and the second subscription dataset, one or more subscribers as a churn-risk. Report the one or more subscribers identified as a churn-risk.

A consumer interaction agent management platform can be provided to facilitate the management of consumer interaction agents. The consumer interaction agent management platform can enable an analyst to obtain a performance summary of a consumer interaction agent representing how accurately the consumer interaction agent predicts the intent of consumer interactions it receives. The consumer interaction agent management platform may also provide various mechanisms for automatically creating training data for a particular intent. The consumer interaction agent management platform may further provide a mechanism for visualizing the extent to which a word impacts the intent predicted for a phrase that includes the word.

In an approach to improve multi-data center environments by minimizing the environmental impact of workloads in multi-data center environments embodiments migrate at least a portion of one or more workloads between one or more data centers automatically to maximize a usage of renewable energy based on a predetermined threshold score of input power and a combination of renewal energy sources. Further, embodiments dictate, by a policy engine, where at least a portion of the one or more workloads can be hosted. Additionally, embodiments control, by a scheduling engine, how, when, and where at least a portion of the one or more workloads will migrate, and perform data replication to migrate data between a plurality of data center locations.

Systems, apparatuses, and methods for implementation of an inference or prediction process using a recurrent neural network (RNN) that is particularly advantageous for low-latency applications. Embodiments introduce an implementation of a recurrent neural network-based system which results in a fixed inference time (i.e., a constant computation time to perform an inference stage) that is independent of input data sequence length. Embodiments may be used to implement real-time data mapping and management and perform an inference strategy that enables the system to be used for serving different types of models, including sequential deep neural networks for low latency (i.e., real-time, or close to real-time) applications.

A method for providing unequal allocation of rights among agents while operating according to fair principles, comprising assigning a hierarchal rank to each agent; providing a synthetic economic value to a first set of agents at the a high level of the hierarchy; allocating portions of the synthetic economic value by the first set of agents to a second set of agents at respectively different hierarchal rank than the first set of agents; and conducting an auction amongst agents using the synthetic economic value as the currency. A method for allocation among agents, comprising assigning a wealth generation function for generating future wealth to each of a plurality of agents, communicating subjective market information between agents, and transferring wealth generated by the secure wealth generation function between agents in consideration of a market transaction. The method may further comprise the step of transferring at least a portion of the wealth generation function between agents.

An AI-based process monitoring system access a plurality of data sources having different data formats to collect and analyze KPI data and shortlist KPIs that are to be used for determining the impact of automation of an automated process or sub-process. Information regarding an automated process is received and KPIs associated with the process and sub-processes of the process are identified. The identified KPIs are put through an approval process and the approved KPIs are presented to a user for selection. The user-selected KPIs are evaluated based on classification, ranking and sentiments associated therewith. The evaluations are again presented to the user along with a set of questionnaires wherein each of the questions has a dynamically controlled weight associated therewith. Based at least on the weights and user responses, a subset of the evaluated KPIs are shortlisted for use in evaluating the impact of process automation.