The present disclosure describes transaction-enabling systems and methods. A system can include a facility including a core task including a customer relevant output and a controller. The controller may include a facility description circuit to interpret a plurality of historical facility parameter values and corresponding facility outcome values and a facility prediction circuit to operate an adaptive learning system, wherein the adaptive learning system is configured to train a facility production predictor in response to the historical facility parameter values and the corresponding outcome values. The facility description circuit also interprets a plurality of present state facility parameter values, wherein the trained facility production predictor determines a customer contact indicator in response to the plurality of present state facility parameter values and a customer notification circuit provides a notification to a customer in response.

A messaging system provides recommendations of content that account holders of the messaging system might be interested in engaging with. In order to determine what to recommend, the messaging system generates a model of account holder engagement behavior organized by type of engagement. The model parameters are trained on differences between expected engagement behavior based on past data and actual engagement behavior, and include a set of common factor matrices that are trained using data from more than on engagement type. As a consequence, engagement behavior of other account holders with respect to other types of engagements different than the one sought to be recommended serves as a partial basis for determining what engagements of the sought-after type are recommended.

A system and method for in-person proximity matching that allows a plurality of user electronic devices to identify and match with one another based on a compatibility profile. The matching is done using a near-field communication protocol, such as Bluetooth or Wi-Fi. The invention allows matching of users when they are within the near proximity, which is defined as approximately 1000 meters.

The systems and methods disclosed herein comprise computer-based platforms configured for automated early-stage application security monitoring for allowing users (e.g., application developers) to make decisions at the early stage of the application development.

A method for generating an electronic file associated with health care professionals (HCPs). The method includes receiving health information from a covered entity computing system and a file generation request from a user computing device. The method further includes matching HCP information with the health information and determining one or more statistical values based on at least one of the matched HCP information or the matched health information. The method further includes generating the electronic file including the one or more statistical values and at least a portion of the matched HCP information and providing the file to the destination address of the file generation request. The electronic file is generated as the file type identified by the file generation request, and is structured based on at least one of the file generation request or the file destination.

A data processing system for machine-learning driven data analysis implements obtaining digital healthcare service provider information associated with one or more digital healthcare service providers and query parameters information from a user searching for digital healthcare service providers that may provide digital healthcare services to employees of the user. The system analyzes query parameter information using a first machine learning model to obtain category information. The system analyzes the category information and the digital health service provider information to predict digital healthcare service providers that provide services that the user may be interested in provided to the employees. These predictions are provided to the user as digital healthcare service recommendations.

A data processing system for machine-learning driven data analysis implements obtaining digital healthcare service provider information associated with one or more digital healthcare service providers and query parameters information from a user searching for digital healthcare service providers that may provide digital healthcare services to employees of the user. The system analyzes query parameter information using a first machine learning model to obtain category information. The system analyzes the category information and the digital health service provider information to predict digital healthcare service providers that provide services that the user may be interested in provided to the employees. These predictions are provided to the user as digital healthcare service recommendations.

Computer-implemented methods, computer-readable storage media storing instructions and computer systems for labeling significant locations based on contextual data can be implemented to perform operations that include determining a location of a computing device, and determining a label for the determined location based on contextual data associated with the significant location. The location can be a significant location that has meaning to a user of the device.

Systems and methods are provided for sharing a screen from a mobile device. For example, a method includes receiving, at a second mobile device, an image of a screen captured from a first mobile device and determining whether to trigger an automated action. The method may also include displaying, responsive to not triggering the automated action, annotation data generated for the image with the image on a display of the second mobile device, the annotation data including at least one visual cue corresponding to content in the image relevant to a user of the second mobile device. The method may further include, responsive to triggering the automated action, determining that a mobile application associated with the image is installed on the second mobile device and replaying user input actions received with the image on the second mobile device starting from a reference screen associated with the mobile application.

Disclosed herein is a method for facilitating generation of real estate descriptions for real estate assets, in accordance with some embodiments. The method may include a step of receiving, using a communication device, real estate information of a real estate asset from a user device, a step of analyzing, using a processing device, the real estate information, a step of generating, using the processing device, a real estate description for the real estate asset using a machine learning model based on the analyzing, a step of receiving, using the communication device, a keyword relevant in a real estate industry from the user device, a step of generating, using the processing device, an optimized real estate description for the real estate asset based on the keyword and the real estate description, and storing, using a storage device, the optimized real estate description.