Systems and methods for enhanced system response and analysis based on artificial intelligence (AI) and real-time mental state analyses

1 . A method implemented by a system of one or more computers, the method comprising:

receiving, via the system, a request associated with a user, the request being received from a subscriber system of a plurality of subscriber systems, wherein an individual subscriber system is associated with a back-end of a first application or web service executing on a user device of one or more user devices associated with the user, and wherein the request is indicative of a request for behavioral response information;

accessing a user profile indicative of the user's mental state, the user profile aggregating disparate historical information associated with the user, and the user profile being associated with a multi-dimensional feature vector clustered within a learned multi-dimensional feature space;

triggering aggregation of real-time information within a threshold window of time, the real-time information being obtained, at least, via a second application executing on the user device, the second application analyzing data derived from sensors and/or user interactions with the user device, the second application forming the real-time information based on the analyses,

wherein the second application is triggered, by the system, to transform raw sensor data from the sensors into insights extracted from the raw sensor data, the raw sensor data reflecting sensitive information associated with the user including biometric data, wherein the user device is restricted from transmitting the raw sensor data,

and wherein, the system, iteratively refines the learned multi-dimensional feature space via promoting the real-time information into a durable portion of the user profile and re-calculates similarity computations for, at least, a cohort of behaviorally proximate neighbors based on the durable portion; and

responding to the request based on the user profile and real-time information, the response being formed using one or more machine learning models, and wherein the response is configured to inform presentation of information via the first application or web service.

2 . The method claim 1 , wherein the real-time information is indicative of a measure of persons proximate to the user, the measure being based on wireless information from wireless sensors proximate to the user.

3 . The method of claim 1 , wherein aggregating real-time information includes:

causing communications between the second application and a separate system proximate to the user, the separate system being included in a vehicle of the user, and the communications reflecting operation information associated with the vehicle,

wherein information included in, or derived from, the communications is received via the system.

4 . The method of claim 3 , wherein operation information associated with the vehicle includes eye-tracking information or verbal speech metrics associated with speech of the user.

5 . The method of claim 1 , wherein the user interactions with the user device indicate measures associated with user input, and wherein the user input includes one or more of touch screen input, speech input, keyboard input, or interactions with software executing on the user device.

6 . The method of claim 1 , wherein the real-time information indicates calendared events and/or user location.

7 . The method of claim 1 , wherein responding to the request comprises:

determining one or more insights extracted from the user profile and the real-time information, wherein an individual insight reflects one or more of a stress level, information indicative environmental context, or a measure indicative of receptiveness.

8 . The method of claim 7 , wherein the information indicative of environmental context reflects a location of the user device, a measure of persons proximate to the user device, or known user devices of other users who are proximate to the user device.

9 . The method of claim 1 , wherein responding to the request comprises:

identifying, based on the user profile and the real-time information, a content item of a plurality of content items; and

causing presentation of the identified content item via the first application, wherein the system routes the content item to the subscriber system for inclusion in the first application.

10 . The method of claim 1 , wherein the subscriber system is associated with navigation, and wherein the responding to the request comprises instructing the subscriber system to adjust a route generated via the subscriber system.

11 . The method of claim 1 , wherein historical information includes one or more of biometric information, user responses to questionnaires, user responses to personality profiles and/or psychological assessment tests, ACE questionnaires, Enneagrams, attachment styles assessments, user reactions to activities and/or prompts, psychological profiling, psychological history, family history, history of associates, online activities.

12 . The method of claim 1 , wherein the response indicates the user is stressed above a baseline.

13 . The method of claim 1 , wherein the response indicates the user is less stressed than a baseline.

14 . The method of claim 1 , wherein the user profile is adjusted or refined over time based on new information associated with the user.

15 . A system comprising one or more processors and non-transitory computer storage media storing instructions that when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving, via the system, a request associated with a user, the request being received from a subscriber system of a plurality of subscriber systems, wherein an individual subscriber system is associated with a back-end of a first application or web service executing on a user device of one or more user devices associated with the user, and wherein the request is indicative of a request for behavioral response information;

accessing a user profile indicative of the user's mental state, the user profile aggregating disparate historical information associated with the user, and the user profile being associated with a multi-dimensional feature vector clustered within a learned multi-dimensional feature space;

triggering aggregation of real-time information within a threshold window of time, the real-time information being obtained, at least, via a second application executing on the user device, the second application analyzing data derived from sensors and/or user interactions with the user device, the second application forming the real-time information based on the analyses,

wherein the second application is triggered, by the system, to transform raw sensor data from the sensors into insights extracted from the raw sensor data, the raw sensor data reflecting sensitive information associated with the user including biometric data, wherein the user device is restricted from transmitting the raw sensor data,

and wherein, the system, iteratively refines the learned multi-dimensional feature space via promoting the real-time information into a durable portion of the user profile and re-calculates similarity computations for, at least, a cohort of behaviorally proximate neighbors based on the durable portion; and

responding to the request based on the user profile and real-time information, the response being formed using one or more machine learning models, and wherein the response is configured to inform presentation of information via the first application or web service.

16 . The system of claim 15 , wherein the real-time information is indicative of a measure of persons proximate to the user, the measure being based on wireless information from wireless sensors proximate to the user.

17 . The system of claim 15 , wherein aggregating real-time information includes:

causing communications between the second application and a separate system proximate to the user, the separate system being included in a vehicle of the user, and the communications reflecting operation information associated with the vehicle,

wherein information included in, or derived from, the communications is received via the system.

18 . The system of claim 15 , wherein responding to the request comprises:

determining one or more insights extracted from the user profile and the real-time information, wherein an individual insight reflects one or more of a stress level, information indicative environmental context, or a measure indicative of receptiveness.

19 . A method performed by one or more processors of a user device associated with a user, the method comprising:

receiving, at the user device via an operating-system mediated interface, a request associated with the user, the request being received from a subscriber component associated with a client application executing on the user device or from a back-end associated with the client application, the request being indicative of behavioral response information;

accessing, at the user device, a user profile indicative of the user's mental state, the user profile aggregating disparate historical information associated with the user and being positioned, via a multi-dimensional feature vector, within a learned multi-dimensional feature space;

triggering, at the user device, aggregation of real-time information within a threshold window of time, the real-time information being obtained via operating-system services by a second application or library executing on the user device that analyzes data derived from sensors and/or user interactions with the user device and forms the real-time information based on the analyses,

wherein the second application transforms raw sensor data from the sensors into insights extracted from the raw sensor data, the raw sensor data reflecting sensitive information associated with the user including biometric data, wherein the user device is restricted from transmitting the raw sensor data,

and wherein the learned multi-dimensional feature space is iteratively refined via promoting the real-time information into a durable portion of the user profile and similarity computations for, at least, a cohort of behaviorally proximate neighbors are re-calculated based on the durable portion;

and responding to the request by generating, on the user device, a response based on the user profile and the real-time information, the response being configured to inform presentation of information via the client application, and the response being formed using one or more machine learning models, wherein the response is routed to the client application or to the back-end associated with the client application.

20 . The method of claim 19 , wherein the real-time information includes a measure of persons proximate to the user derived from wireless information exposed by operating-system services.

21 . The method of claim 19 , further comprising receiving, at the user device over a secured pairing, summarized metrics or insights from a companion wearable device, and incorporating the summarized metrics or insights into the real-time information.

22 . The method of claim 19 , wherein data derived from sensors includes biometrics reflecting at least a stress response, and wherein raw biometric information remains restricted to the user device and is not transmitted off the device.