Abstract: A server device may receive, from a first user device, a first set of information regarding a first accident involving a first vehicle, and from a second user device, a second set of information regarding a second accident involving a second vehicle. The first user device may relate to a first user associated with a first policy issued by a first policy provider. The second user device may relate to a second user associated with a second policy issued by a second policy provider. The server device may determine that the first accident corresponds to the second accident, obtain first policy data relating to the first policy, and second policy data relating to the second policy, and cause the first policy data to be provided to the second user device, and the second policy data to be provided to the first user device.

Abstract: Embodiments disclosed herein generally relate to a method and system of determining an overall sentiment of a facility. A computing system receives a video stream, including a plurality of frames, of one or more patrons in a facility over a first time period. The video stream includes data indicative of a sentiment of each of the one or more patrons. The computing system parses the plurality of frames to determine the sentiment of the patron based at least on audio and visual cues of the patron captured in the video stream during the first time period. The computing system aggregates one or more sentiments corresponding to the one or more patrons in a data set indicative of an overall sentiment of the facility. The computing system generates a sentiment value corresponding to the overall sentiment of the facility. The computing system outputs the overall sentiment of the facility.

Abstract: A device may receive meeting data associated with a first meeting, the first meeting having previously occurred. The device may obtain, based on the meeting data, data identifying at least one individual associated with the first meeting and data identifying at least one topic associated with the first meeting. In addition, the device may identify a second meeting based on the at least one individual or the at least one topic, the second meeting having not yet occurred. The device may provide, to a user device associated with the second meeting and based on identifying the second meeting, at least a portion of the meeting data associated with the first meeting.

Abstract: Systems and methods are provided for providing a customized user experience. Providing a customized user experience may include receiving, from a graphical user interface displayed on a mobile device a user input indicative of a preferred level of interaction by the user, and monitoring, by a sensor, a facial expression of the user. Then, a first preference metric may be assigned to the user based on the monitored facial expression. Providing a customized user experience may further include monitoring, by a sensor, a behavior of the user, assigning a second preference metric based on the monitored behavior, and aggregating at least the user input, the first preference unit, and the second preference metric to generate a preference score of the user. The preference score may be stored in a central database, displayed on a remote device, and used to modify a customer service experience.

Abstract: Systems and methods are provided for providing a customized user experience. Providing a customized user experience may include receiving, from a graphical user interface displayed on a mobile device a user input indicative of a preferred level of interaction by the user, and monitoring, by a sensor, a facial expression of the user. Then, a first preference metric may be assigned to the user based on the monitored facial expression. Providing a customized user experience may further include monitoring, by a sensor, a behavior of the user, assigning a second preference metric based on the monitored behavior, and aggregating at least the user input, the first preference unit, and the second preference metric to generate a preference score of the user. The preference score may be stored in a central database, displayed on a remote device, and used to modify a customer service experience.

Abstract: Multi-factor authentication systems and methods are provided that include receiving a request to authenticate a user of a mobile device. The request for authentication may include credential information associated with the user and vehicle data. A determination may be made regarding whether the vehicle data was obtained from a vehicle via the mobile device. The received vehicle data and received credential information may be compared to stored data. When there is a match between the received vehicle data and received credential information and corresponding stored data, a notification may be provided to the user device, indicating that the user has been authenticated.

Abstract: Embodiments disclosed herein generally relate to a method and system of generating text input via facial recognition. A computing system receives a video stream of a user operating an application on a client device. The video stream includes a time series of images of the user. The computing system parses the video stream to identify one or more visual cues of the user. The computing system identifies a current page of the application. The computing system maps the identified on or more visual cues to an operation available on the current page of the application. The computing system executes the mapped operation.

Abstract: Embodiments disclosed herein generally relate to a system and method for detecting fraudulent computer activity. A computing system generates a plurality of synthetic identities. Each of the plurality of synthetic identities mimics information associated with a verified identity. The computing system receives, from a user, an input attempt. The input attempt includes a synthetic identity of the plurality of synthetic identities. The computing system compares input information in the input attempt to the plurality of synthetic identities. The computing system determines that the input information in the input attempt includes information from the plurality of synthetic identities, if it does, the computing system rejects the input attempt.

Abstract: A user device may receive sensor data relating to one or more physical objects, transmit the sensor data to a server, receive a user profile relating to a user of the device, identify a user interface element corresponding to an application, modify the user interface element based on the user profile, and display the modified user interface element. A server may receive data relating to one or more physical objects, identify the one or more design patterns based on the one or more physical objects, create a user profile, update the user profile, receive application data relating to one or more applications running on a device remote from the server, identify a user interface element corresponding to the one or more applications running on the device, modify the user interface element based on the updated user profile, and transmit the modified user interface element to the device.

Abstract: Embodiments disclosed herein generally relate to a method and system of determining an overall sentiment of a facility. A computing system receives a video stream, including a plurality of frames, of one or more patrons in a facility over a first time period. The video stream includes data indicative of a sentiment of each of the one or more patrons. The computing system parses the plurality of frames to determine the sentiment of the patron based at least on audio and visual cues of the patron captured in the video stream during the first time period. The computing system aggregates one or more sentiments corresponding to the one or more patrons in a data set indicative of an overall sentiment of the facility. The computing system generates a sentiment value corresponding to the overall sentiment of the facility. The computing system outputs the overall sentiment of the facility.

Abstract: A system for verifying a user identity. The system comprises one or more memory devices storing instructions and one or more processors configured to execute the instructions. The processors are configured to receive information associated with an account of a user. The processors are further configured to generate a first profile, where the first profile being related to the user. The processors also receives an indication that the account is accessed by an accessor through an accessor device; and receive, from the accessor device, identity data comprising a plurality of data subsets associated with the accessor. The processors are configured to store the data subsets in respective clusters. The processors are further configured generate cluster analyses by analyzing the data subsets in respective clusters; and output the cluster analyses to node instances that weighs the cluster analyses outputs.

Abstract: A user device may receive sensor data relating to one or more physical objects, transmit the sensor data to a server, receive a user profile relating to a user of the device, identify a user interface element corresponding to an application, modify the user interface element based on the user profile, and display the modified user interface element. A server may receive data relating to one or more physical objects, identify the one or more design patterns based on the one or more physical objects, create a user profile, update the user profile, receive application data relating to one or more applications running on a device remote from the server, identify a user interface element corresponding to the one or more applications running on the device, modify the user interface element based on the updated user profile, and transmit the modified user interface element to the device.

Abstract: Embodiments disclosed herein generally relate to a system and method for detecting fraudulent computer activity. A computing system generates a plurality of synthetic identities. Each of the plurality of synthetic identities mimics information associated with a verified identity. The computing system receives, from a user, an input attempt. The input attempt includes a synthetic identity of the plurality of synthetic identities. The computing system compares input information in the input attempt to the plurality of synthetic identities. The computing system determines that the input information in the input attempt includes information from the plurality of synthetic identities, if it does, the computing system rejects the input attempt.

Abstract: Embodiments disclosed herein generally relate to a method and system of generating text input via facial recognition. A computing system receives a video stream of a user operating an application on a client device. The video stream includes a time series of images of the user. The computing system parses the video stream to identify one or more visual cues of the user. The computing system identifies a current page of the application. The computing system maps the identified on or more visual cues to an operation available on the current page of the application. The computing system executes the mapped operation.

Abstract: Embodiments disclosed herein generally relate to a method and system of determining an overall sentiment of a facility. A computing system receives a video stream, including a plurality of frames, of one or more patrons in a facility over a first time period. The video stream includes data indicative of a sentiment of each of the one or more patrons. The computing system parses the plurality of frames to determine the sentiment of the patron based at least on audio and visual cues of the patron captured in the video stream during the first time period. The computing system aggregates one or more sentiments corresponding to the one or more patrons in a data set indicative of an overall sentiment of the facility. The computing system generates a sentiment value corresponding to the overall sentiment of the facility. The computing system outputs the overall sentiment of the facility.

Abstract: Embodiments disclosed herein generally relate to a system and method for detecting fraudulent computer activity. A computing system generates a plurality of synthetic identities. Each of the plurality of synthetic identities mimics information associated with a verified identity. The computing system receives, from a user, an input attempt. The input attempt includes a synthetic identity of the plurality of synthetic identities. The computing system compares input information in the input attempt to the plurality of synthetic identities. The computing system determines that the input information in the input attempt includes information from the plurality of synthetic identities, if it does, the computing system rejects the input attempt.

Abstract: A device may receive meeting data associated with a first meeting, the first meeting having previously occurred. The device may obtain, based on the meeting data, data identifying at least one individual associated with the first meeting and data identifying at least one topic associated with the first meeting. In addition, the device may identify a second meeting based on the at least one individual or the at least one topic, the second meeting having not yet occurred. The device may provide, to a user device associated with the second meeting and based on identifying the second meeting, at least a portion of the meeting data associated with the first meeting.

Abstract: A system for verifying a user identity is disclosed. The system is configured to generate a first profile related to the user and receive an indication that the account is accessed by an accessor through an accessor device. The system receives, from the accessor device, identity data associated with the accessor. The system is configured to store the identity data subsets in clusters, analyze the clusters, and output the cluster analyses to node instances that weighs the cluster analyses outputs. The system also generates a second profile related to the accessor based on the received identity data and weighted cluster analysis. The system determines a likelihood factor that the accessor is the user based on a comparison of the first profile and the second profile.