A method of advanced technology allowing to find, coordinate and decide meeting details from larger communications, using neuro linguistic programming to predict and automatically set meeting among multiple individuals. The system utilizes relevant snippets from unstructured data to coordinate the optimal meeting and associated factors. Meeting information is fully edited by natural English, different actions on the calendar invite itself like responding with “No” will activate back end to reschedule with guests. Multiple guests can schedule with Laura and multiple subjects can be in the text which will be understood and parsed by the AI. Once the assistant is added into a messenger platform the assistant will send the users availability to the guest and the guest can answer in natural English or manually press which availability works best for them.

Methods and systems for management of calendar data are described herein.

Methods and systems for management of calendar data are described herein.

An adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish ongoing communications with consumers so as to maximize the relationship between the consumer and a given brand. The system has a connection management services layer which determines what communications should be established and how they should be established, an initiation management services layer which determines when communications should be established, and a user management services layer which stores information about consumers and brands for determination of when and how communications should be established. Certain of these services have machine learning algorithms incorporated into them trained to perform analyses of the particular type of operation handled by that service.

The outputs of each service can be used as inputs to other services, such that a network of machine learnings algorithms is created which determines when and how to establish ongoing communications with consumers.

An adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish ongoing communications with consumers so as to maximize the relationship between the consumer and a given brand. The system has a connection management services layer which determines what communications should be established and how they should be established, an initiation management services layer which determines when communications should be established, and a user management services layer which stores information about consumers and brands for determination of when and how communications should be established. Certain of these services have machine learning algorithms incorporated into them trained to perform analyses of the particular type of operation handled by that service.

The outputs of each service can be used as inputs to other services, such that a network of machine learnings algorithms is created which determines when and how to establish ongoing communications with consumers.

Arrangements for payment and recommendation control are provided. In some aspects, an event trigger and contextual data may be received from, for instance, a user device. In response to the event trigger, one or more requests for external entity data may be generated and transmitted to one or more external entity computing systems. External entity response data may be received and analyzed, with the contextual data, using machine learning, to identify one or more recommended options for a user. The one or more recommended options may be transmitted to a user computing device. In some examples, user selection of a first option may be received and a communication session may be initiated with a first external entity computing system. A scheduling request may be transmitted to the first external entity computing system and a scheduling confirmation may be received from the first external entity computing system.

Arrangements for payment and recommendation control are provided. In some aspects, an event trigger and contextual data may be received from, for instance, a user device. In response to the event trigger, one or more requests for external entity data may be generated and transmitted to one or more external entity computing systems. External entity response data may be received and analyzed, with the contextual data, using machine learning, to identify one or more recommended options for a user. The one or more recommended options may be transmitted to a user computing device. In some examples, user selection of a first option may be received and a communication session may be initiated with a first external entity computing system. A scheduling request may be transmitted to the first external entity computing system and a scheduling confirmation may be received from the first external entity computing system.

Computer-implemented systems and methods for the sale of consumer services. Predictions are made based on the behaviors, preferences, assets, identifying characteristics, and other attributes associated with customers and merchants. In one implementation, a prediction is made as to whether a customer is likely to request a service and whether a merchant is likely to be selected by the customer to provide the service. In another implementation, the calendars of a merchant and customer are automatically updated to account for the customer's late arrival to an appointment at the merchants location. In yet another implementation, a customer purchases an appointment for a service from another customer that has the appointment scheduled with a merchant providing the service.

A landing pad receives and stores packages delivered from an aerial vehicle and awaiting pickup from an aerial vehicle. The landing pad can be placed outside of a window and can contain a transmitter for sending out an identification signal via radio frequency to aid aerial vehicles in finding the landing pad. The landing pad contains a landing platform with a trapdoor that leads to a storage compartment. The trapdoor can be configured to only open when it receives a signal from an authorized aerial vehicle. The storage compartment can be accessed via a storage compartment door which can contain a locking mechanism. The storage compartment can be climate controlled. The landing pad can also have a transmitter that emits sounds to discourage animals from nesting on or near the landing pad. The landing pad can also include a solar power generator as a source of electrical energy.

A system and method are disclosed for helping a user determine whether a vehicle is subject to a safety recall and assisting the user with addressing incomplete safety recalls. A vehicle identification number (VIN) may be extracted from an image of a vehicle captured by a user electronic device and used to request safety recall information from a remote information system, which may provide a list of recalls associated with the vehicle. A list of nearby service centers may be identified based on the physical location of the user electronic device, and service appointments to address any incomplete recalls may be scheduled, either automatically or in response to user input.