United Services Automobile Association (usaa)

Uipco, LLC

Mathew Cyriac Kottoor

Joseph H Louwagie, Iii

Reynaldo Medina, Iii

Nathan Lee Post

Noe Alberto Martinez

Subhalakshmi Selvam

Keegan Patrick Hayes

Anto Chirayil Thomas

Jennifer Marie Chandler-Bradley

Nina Cooper

Charlotte Thomas Creech

Jennifer Dawn Ayala

Thomas Mercer Harper

Emily Nicole Van Santen

Gideon B Luck

Pradeep R Mangalagiri

Iris Jordan

Andrew Flores

A system may include one or more detectors configured to generate detector data based on signals received from one or more tags integrated in or disposed on one or more items. The system may include a processor configured to: receive the detector data; determine a first set of identification information corresponding to a first item of the one or more items based on the detector data; receive a list of tagged items for a first location, and the list of tagged items comprises a second set of identification information corresponding to the one or more items; identify a theft incident for the first item based on a comparison of the first and second sets of identification information; automatically send a notification relating to the theft incident to one or more devices; and determine one or more insurance policy decisions for the first item based on the theft incident.

Systems and methods for continuously monitoring items

Methods and systems described herein are directed to obtaining various types of information that can provide an accounting for an individual's legacy that can be replayed to learn about objects and/or experiences associated with the individual. A personal legacy accountant can generate a legacy profile using automatically obtained public records and personal records supplied by the individual, and afford the individual an opportunity to contextualize records for the profile. Through this contextualization, the individual can selectively define one or more perspectives for her legacy.

Personal legacy accounting and remembrance

A computing system acquires a plurality of gig-income models for a plurality of gig-workers, and each of the plurality of gig-income models includes a corresponding expected income for a respective gig-worker of the plurality of gig-workers over a period of time. The computing system identifies groups of gig-workers to join an income float pool based on the gig-income models of the gig-workers. The computing system transfers funds into or out from an account associated with a gig-worker in the income float pool in response to detecting, from one or more data sources, a difference between an actual income and an expected income of the gig-worker during an additional period of time. Thus, the gig-worker receives a relatively stable income.

Systems and methods for dynamically providing float funds for gig-economy workers

Implementations ingest records across multiple accounts hosted by different service providers and augment the records with metadata. For example, ingesting can include processing the records to identify transactions in the records and to discover additional aspects of the transactions. In some implementations, metadata can be used to augment the identified transactions in the records, where metadata can include a category, a digital receipt, a user tag such as a geotag, and other suitable metadata. The ingesting and augmenting the records can populate a coordination data structure with identified transactions and their associated data elements. These identified transactions can then be queried and a result set of transactions that span the different user accounts can be returned. In some implementations, the transactions can be queried using the augmented metadata, or other suitable pieces of information for the transactions.

Ingesting, augmenting, and querying records across user accounts

Growing community of inventors

San Antonio, TX, United States of America

Mathew Cyriac Kottoor