The invention includes systems, methods, and software applications for centrally maintaining information and automatically distributing relevant portions of the information to remote users. In one embodiment, a central server stores the information, which is maintained on the central server. Periodically, or each time the server information is updated, the server identifies the portion of the information that is relevant to each user and downloads the relevant portion of information to each user, for example to a mobile device such as a Blackberry™. The invention may be used to maintain and timely distribute information related to emergency response procedures, sales or servicing schedules, and delivery schedules, among other things.

In one embodiment, a method for automatic inference of meeting attendance is provided. The method comprises sending a calendar request to a plurality of users that are invited to a meeting. The method further comprises receiving from each user of the plurality, a unique string identifying the user. The method further comprises generating a lookup table identifying the users of the plurality and their respective unique strings. The method further comprises receiving a first string broadcasted by a first user during the meeting. The method further comprises, responsive to determining that the broadcasted first string does not match one of the unique strings in the lookup table, performing an action to prevent the first user from receiving meeting content determined to be confidential.

An online tool, including a technology application that connects workers with customers that have immediate service needs. This tool provides immediate solutions to customers in need of a service and an economic opportunity to workers around the world. This tool seeks to connect expertise with opportunity at massive scale.

The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Embodiments of the present disclosure are directed to, among other things, generating reminders based on information from applications. For example, triggering events such as other users and/or locations can be used to configure reminders. Additionally, in some examples, reminders can be generated based at least in part on user interaction with an application, where state information can be saved and associated with the reminders.

A user may be directed to the nail application (e.g., a mobile application that provides the various augmented reality and booking features discussed herein) via interactions with a social media site. For example, a user may browse Facebook and see a friend's post or advertisement regarding a nail design, or more generally, some artwork that the user feels would look nice as a nail design. The user may select the artwork and be redirected to the nail application to begin an augmented reality testing of one or more nail artwork designs and/or schedule treatments. In some embodiments, the social media website utilizes an API provided by the data center (e.g. the entity that coordinates the treatment booking process and provides augmented reality software to the users) so that the user can “Touch to try-on” a particular design team in social media by clicking on the design.

Systems and apparatuses include one or more processing circuits comprising one or more memory devices coupled to one or more processors, the one or more memory devices configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to: receive vehicle information including operating conditions and historical vehicle information, develop a vehicle model using a machine learning engine that receives the vehicle information, determine a fleet failure probability based on the vehicle model and fleet information including fleet usage and fleet vehicle types, and determine a predictive maintenance schedule based on the fleet failure probability.

Artificial intelligence (Al) based technologies for improving patient appointment scheduling and inventory management are disclosed herein. An example method includes receiving, at a server including a natural language processing (NLP) model, an appointment request from a user. The example method further includes initiating, based on the appointment request, a patient appointment data stream including verbal responses from the user regarding an appointment of the user. The example method further includes applying, while simultaneously receiving the patient appointment data stream, the NLP model to the verbal responses from the user to output (i) textual transcriptions and (ii) intent interpretations. The example method further includes querying a scheduling database to determine a matching appointment that satisfies a distance threshold, a date threshold, a service threshold, and an inventory threshold. The example method further includes causing a user device of the user to convey the matching appointment to the user.

A life management system receives data from a client device worn by a user, the data comprising biotelemetry data and activity data collected about a user wearing the client device. The life management system generates snapshot information using information from a group consisting of: the biotelemetry data, activity data, social data associated with the user, and user profile information associated with the user. The life management system generates a recommendation using portions of the snapshot information, and updates the snapshot information with the recommendation. The life management system executes a recommendation associated with the snapshot information in accordance with the user controls associated with the user.

A system for management of networked collaboration comprising a process server communicatively coupled to a content server and a collaborative workspace server. The process server hosts a process configured to invoke a first collaborative workspace method that invokes a first class on the content server. The first class is configured to send, to the collaborative workspace server, a request to create a new collaborative object. The collaborative workspace server hosts a collaborative workspace accessible by a plurality of users. The collaborative workspace server creates the new collaboration object responsive to the request to create the new collaborative object. The process server creates first proxy object that points to the new collaboration object. The content server creates a first reference object that links to the new collaborative object. The collaborative workspace server receives, processes and responds to actions on the first proxy object.