US 12,332,928 B2
Systems and methods for analysis of user telematics data using generative AI
Aaron Williams, Congerville, IL (US); Scott T. Christensen, Salem, OR (US); Ryan Gross, Normal, IL (US); and Joseph P. Harr, Bloomington, IL (US)
Assigned to STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY, Bloomington, IL (US)
Filed by STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY, Bloomington, IL (US)
Filed on May 12, 2023, as Appl. No. 18/196,691.
Claims priority of provisional application 63/460,675, filed on Apr. 20, 2023.
Claims priority of provisional application 63/453,604, filed on Mar. 21, 2023.
Claims priority of provisional application 63/450,224, filed on Mar. 6, 2023.
Claims priority of provisional application 63/447,983, filed on Feb. 24, 2023.
Prior Publication US 2024/0289362 A1, Aug. 29, 2024
Int. Cl. G06F 16/33 (2019.01); G06F 16/3329 (2025.01); G06Q 40/08 (2012.01); G06Q 50/00 (2012.01)
CPC G06F 16/3329 (2019.01) [G06Q 40/08 (2013.01); G06Q 50/01 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for analyzing user data, the computer-implemented method comprising:
determining, by one or more processors, a user identity for a user at a generative artificial intelligence (AI) model based upon a user action;
retrieving, by the one or more processors and based upon at least the user identity, user data from at least one of one or more publicly accessible sources or one or more privately accessible sources;
determining, by the one or more processors and based upon at least the user data, one or more personalization characteristics associated with at least an information retention rate for the user via the generative AI model, wherein:
the information retention rate is indicative of a baseline rate for user understanding of information, and
the one or more personalization characteristics are predicted to affect the user understanding of the information based upon the information retention rate; and
generating, by the one or more processors, a personalized dialogue output for the user via the generative AI model, the personalized dialogue output including a plan based upon at least the one or more personalization characteristics.