Abstract: Disclosed are techniques for classifying inquiries and providing recommended actions. These techniques identify or generate a data model that receives and classifies an inquiry into at least one class in real-time or nearly real-time. One or more actions may be determined based at least in part on the at least one class and presented in a user interface to a user who first submitted the inquiry.

Abstract: Disclosed are techniques for automatic generation of software application code. These techniques identify or generate a data model in a first programming language. At least one rule is identified or generated from the data model. This at least one rule is tokenized into a plurality of subparts based at least in part upon a second programming language. A rule hierarchy at which the plurality of sub-parts is located is determined based in part or in whole upon a corresponding class hierarchy of a class with which the at least one rule is associated. A transformed data model is generated in the second programming language using at least the plurality of sub-parts and the rule hierarchy.

Abstract: Disclosed are techniques for classifying inquiries in real-time or nearly real-time. These techniques identify or generate a data model that receives and determine one or more classes for the inquiry in real-time or nearly real-time at least by applying a hierarchical set of rules in the data model to the inquiry. A hierarchical class data structure at least by storing and indexing the one or more classes based in part or in whole upon a hierarchical structure of the one or more classes in a non-transitory computer memory.

Abstract: Disclosed are techniques for automatic generation of software application code. These techniques identify or generate a data model in a first programming language. At least one rule is identified or generated from the data model. This at least one rule is tokenized into a plurality of subparts based at least in part upon a second programming language. A rule hierarchy at which the plurality of sub-parts is located is determined based in part or in whole upon a corresponding class hierarchy of a class with which the at least one rule is associated. A transformed data model is generated in the second programming language using at least the plurality of sub-parts and the rule hierarchy.

Abstract: Disclosed are techniques for classifying inquiries and providing recommended actions. These techniques identify or generate a data model that receives and classifies an inquiry into at least one class in real-time or nearly real-time. One or more actions may be determined based at least in part on the at least one class and presented in a user interface to a user who first submitted the inquiry.

Abstract: Disclosed are techniques for automatic generation of software application code. These techniques identify or generate a data model in a first programming language. At least one rule is identified or generated from the data model. This at least one rule is tokenized into a plurality of subparts based at least in part upon a second programming language. A rule hierarchy at which the plurality of sub-parts is located is determined based in part or in whole upon a corresponding class hierarchy of a class with which the at least one rule is associated. A transformed data model is generated in the second programming language using at least the plurality of sub-parts and the rule hierarchy.

Abstract: Disclosed are techniques for classifying inquiries and providing recommended actions. These techniques identify or generate a data model that receives and classifies an inquiry into at least one class in real-time or nearly real-time. One or more actions may be determined based at least in part on the at least one class and presented in a user interface to a user who first submitted the inquiry.

Abstract: Disclosed are techniques for capturing and classification of digital data and providing recommendations in real-time or nearly real-time. These techniques identify a plurality of agent computing or communication devices in communication with a server and identify a plurality of communications between the plurality of agent computing or communication devices and a plurality of user communication or computing devices of a plurality of users into real-time service data. One or more actions are determined for a communication of the plurality of communications based in part or in whole upon at least one communication class into which the communication is classified. One or more post-classification tasks are performed based in part or in whole upon the one or more actions determined at the recommendation module.