Abstract: Systems and methods for identifying and extracting specific product usage patterns of potential customers and utilizing a machine learning evaluation model to predict the potential customers that are most likely to convert their subscriptions.

Abstract: A method may include obtaining a knowledge graph including entities, and determining, for the knowledge graph, a first state including a first selectable entity subset of the entities that are selectable by a user. The first selectable entity subset may include an entity. The method may further include receiving, from the user and via a graphical user interface (GUI), a selection of the entity from the first selectable entity subset, and responsive to the selection, adding the entity to a report schema. The method further includes restricting, by the GUI, a space of selectable entities addable to the knowledge graph to the first selectable entity subset. The report schema may be used to populate a report. The method may further include, responsive to the selection, transitioning the knowledge graph to a second state including a second selectable entity subset of the entities that are selectable by the user.

Abstract: A method may include obtaining a knowledge graph including entities, and determining, for the knowledge graph, a first state including a first selectable entity subset of the entities that are selectable by a user. The first selectable entity subset may include an entity. The method may further include receiving, from the user and via a graphical user interface (GUI), a selection of the entity from the first selectable entity subset, and responsive to the selection, adding the entity to a report schema. The method further includes restricting, by the GUI, a space of selectable entities addable to the knowledge graph to the first selectable entity subset. The report schema may be used to populate a report. The method may further include, responsive to the selection, transitioning the knowledge graph to a second state including a second selectable entity subset of the entities that are selectable by the user.

Abstract: A method may include obtaining a knowledge graph including entities, and determining, for the knowledge graph, a first state including a first selectable entity subset of the entities that are selectable by a user. The first selectable entity subset may include an entity. The method may further include receiving, from the user and via a graphical user interface (GUI), a selection of the entity from the first selectable entity subset, and responsive to the selection, adding the entity to a report schema. The report schema may be used to populate a report. The method may further include, responsive to the selection, transitioning the knowledge graph to a second state including a second selectable entity subset of the entities that are selectable by the user.

Abstract: A method of automating a workflow may include obtaining a completeness graph including conditions applied to attributes of an entity, determining that a missing attribute subset of the attributes lacks a corresponding value, determining that a condition corresponding to a missing attribute of the missing attribute subset is satisfied, and obtaining a value for the missing attribute. The value may be a result of performing a task in the workflow. The method may further include modifying a state of the entity by assigning the value to the missing attribute to obtain a modified state of the entity.

Abstract: A method to predict a delay involves receiving an open invoice sent by a company to a customer, extracting, using a programmable interface, a set of company data, a set of customer data, and a set of invoice data from a management application (MA) and the open invoice; refining, using a set of algorithms, the set of company data, the set of customer data, and the set of invoice data into a set of invoice attributes, a set of company features, and a set of customer features; predicting a delay in processing the open invoice using a trained model analyzing the set of company features and the set of customer features; updating, at an expiration of a predetermined timespan, the MA to add the delay to a due date of the open invoice by including the set of company features; and updating, at the expiration of the predetermined timespan, the MA to add the delay in processing the open invoice by including the set of customer features.

Abstract: A method to predict a delay involves receiving an open invoice sent by a company to a customer, extracting, using a programmable interface, a set of company data, a set of customer data, and a set of invoice data from a management application (MA) and the open invoice; refining, using a set of algorithms, the set of company data, the set of customer data, and the set of invoice data into a set of invoice attributes, a set of company features, and a set of customer features; predicting a delay in processing the open invoice using a trained model analyzing the set of company features and the set of customer features; updating, at an expiration of a predetermined timespan, the MA to add the delay to a due date of the open invoice by including the set of company features; and updating, at the expiration of the predetermined timespan, the MA to add the delay in processing the open invoice by including the set of customer features.

Abstract: Methods and systems are provided for adapting software applications for download and execution on a variety of different mobile devices which employ different Application Execution Environments. An Application Download Protocol for transferring applications to mobile devices is also provided. Mobile devices can be matched with compatible applications according to functionality required by the applications and functionality provided by the mobile devices. Applications submitted by developers can be automatically matched to application categories, thus facilitating user selection of applications. Data used by applications running on mobile devices can be remotely managed by application developers, allowing developers to remotely control the type and presentation of data on mobile devices without the need for data management servlets to be provided by the developers.

Abstract: Methods and systems are provided for adapting software applications for download and execution on a variety of different mobile devices which employ different Application Execution Environments. An Application Download Protocol for transferring applications to mobile devices is also provided. Mobile devices can be matched with compatible applications according to functionality required by the applications and functionality provided by the mobile devices. Applications submitted by developers can be automatically matched to application categories, thus facilitating user selection of applications. Data used by applications running on mobile devices can be remotely managed by application developers, allowing developers to remotely control the type and presentation of data on mobile devices without the need for data management servlets to be provided by the developers.