A highly immersive, interactive and addictive platform for shopping. The system may provide both an online and retail experience through an immersive environment that enables repeat transactions and enables add-on sales to offers that are completely unique for each customer. The interactive shopping experience generates one or more bundles to any actual or potential user purchase to create a dynamic and favorable shopping experience for the particular user. The bundles are customized for each user based on user history with a merchant, product data, and merchant data, In addition to customizing the bundles, the decision of whether or not to offer one or more bundles is made only confirming that the current time is desirable to make an offer of bundles to the particular user.

A method for providing automated predictive analysis for a case management system is disclosed and includes providing, by a server, a case management system comprising configuration information defining a plurality of case attributes and performance criteria comprising at least one performance criterion, and comprising case management data associated with the plurality of case attributes and a plurality of cases, and automatically determining a projected outcome associated with a performance criterion included in the configuration information. The method also includes identifying a correlation between a case attribute and the projected outcome based on case management data associated with the case attribute and/or case management data associated with the performance criterion, generating a prediction model based on the correlation and providing a prediction relating to the projected outcome based on the correlation.

One example method includes formulating a hypothesis for development of computing model, annotating the hypothesis with ethics metadata, storing the hypothesis and the ethics metadata, in association with each other, in a ledger, performing ‘n’ phases of a development lifecycle for the computing model, annotating each of the ‘n’ phases with ethics metadata specific to the phase, updating the ledger to include the ‘n’ phases and the ethics metadata respectively associated with each of the ‘n’ phases, and calculating an ethics confidence score for the computing model.

One example method includes formulating a hypothesis for development of computing model, annotating the hypothesis with ethics metadata, storing the hypothesis and the ethics metadata, in association with each other, in a ledger, performing ‘n’ phases of a development lifecycle for the computing model, annotating each of the ‘n’ phases with ethics metadata specific to the phase, updating the ledger to include the ‘n’ phases and the ethics metadata respectively associated with each of the ‘n’ phases, and calculating an ethics confidence score for the computing model.

This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for management of one or more organizational hierarchies. In one aspect of the disclosure, a method for managing member information associated with multiple organization hierarchies includes storing member information and a plurality of group models. Each group model of the plurality of group models includes multiple group data structures, multiple group type data structures, and multiple group member data structures. Each group model of the plurality of group models is associated with group hierarchy information that indicates a hierarchy associated with the multiple group data structures associated with the group model. The method further includes sending, to the user device and based on a received access request, first hierarchy information associated with a first group model of the plurality of group models. Other aspects and features are also claimed and described.

This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for management of one or more organizational hierarchies. In one aspect of the disclosure, a method for managing member information associated with multiple organization hierarchies includes storing member information and a plurality of group models. Each group model of the plurality of group models includes multiple group data structures, multiple group type data structures, and multiple group member data structures. Each group model of the plurality of group models is associated with group hierarchy information that indicates a hierarchy associated with the multiple group data structures associated with the group model. The method further includes sending, to the user device and based on a received access request, first hierarchy information associated with a first group model of the plurality of group models. Other aspects and features are also claimed and described.

An apparatus includes a memory, a communication interface in communication with a network, a first processor, and a second process different from the first processor. The first processor configured to receive data from a user device and to separate the data into a first data set including metadata associated with a user of the user device and a second data set including anonymized data associated with a set of actions to be performed on a predetermined schedule. The second processor is configured to receive the second data set from the first processor and a user input associated with a selection of a simulation and at least one additional action otherwise not included in the set of actions. The second processor configured to perform the simulation using the second data set to simulate an acceleration of the predetermined schedule as a result of the at least one additional action.

An apparatus includes a memory, a communication interface in communication with a network, a first processor, and a second process different from the first processor. The first processor configured to receive data from a user device and to separate the data into a first data set including metadata associated with a user of the user device and a second data set including anonymized data associated with a set of actions to be performed on a predetermined schedule. The second processor is configured to receive the second data set from the first processor and a user input associated with a selection of a simulation and at least one additional action otherwise not included in the set of actions. The second processor configured to perform the simulation using the second data set to simulate an acceleration of the predetermined schedule as a result of the at least one additional action.

A demand forecasting method and a demand forecasting apparatus are provided. A preliminary prediction amount corresponding to a part number is obtained based on historical demand data. A demand probability of the part number is calculated based on the preliminary prediction amount. A prediction demand amount corresponding to the part number is obtained based on the historical demand data, the preliminary prediction amount and the demand probability.

Some embodiments provide a non-transitory machine-readable medium that stores a program. The program observes a parameter associated with a computing system. Upon receiving a change associated with the parameter, the program further determines a routine definition from a set of routine definitions associated with the parameter. Each routine definition in the set of routine definitions specifies a set of instructions associated with a particular parameter associated with the computing system. The program also executes the set of instructions specified in the determined routine definition.