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Nayya Health ML Patent for Insurance Recommendations Based on Demographics

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Summary

USPTO granted Patent US12602730B2 to Nayya Health, Inc. on April 14, 2026. The patent covers a machine-learning data processing system that analyzes user demographic information to recommend insurance plan bundles using clustering algorithms and predicted medical consumption. The system generates customized insurance recommendations and presents them via a user interface. The patent contains 20 claims.

What changed

USPTO granted Patent US12602730B2 to Nayya Health, Inc., covering a machine-learning data processing system that recommends insurance plans based on user demographics. The system uses ML clustering to group insured people with similar demographics and generates insurance bundles based on predicted medical consumption. It then customizes recommendations and presents them via a user interface.

Companies developing or operating ML-based insurance recommendation systems should review this patent to assess potential licensing needs or design-around considerations. The patent's broad claims covering demographic-based clustering for insurance recommendations may affect how competitors structure similar offerings.

What to do next

  1. Monitor for patent enforcement actions related to similar insurance recommendation systems
  2. Review licensing options if developing comparable ML-based insurance recommendation technology

Archived snapshot

Apr 14, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Grants

Machine-learning driven data analysis based on demographics, risk, and need

Grant US12602730B2 Kind: B2 Apr 14, 2026

Assignee

Nayya Health, Inc.

Inventors

Sina Chehrazi, Josh Allen Brown, Lisa Renee Carpenter, Akash Magoon, Aman Magoon

Abstract

A data processing system for recommending insurance plans implements obtaining an electronic copy of demographic information associated with a user; analyzing the demographic information with a first machine learning model to recommend a bundle of insurance policies based on the demographic information, wherein the first machine learning model is configured to group insured people having similar demographics into clusters and to generate the bundle of insurance policies based on predicted medical insurance consumption associated with a respective group into which the model predicts that the first user falls; customizing the recommended bundle of insurance policies based on the demographic information associated with the user to generate a customized bundle of insurance policies; generating an insurance recommendation report that presents the customized bundle of insurance policies to the user; and causing a user interface of a display of a computing device associated with the user to present the insurance recommendation report.

CPC Classifications

G06Q 40/08 G06Q 30/0203 G06Q 40/082 G06Q 40/0822 G06N 20/00 G16H 10/60

Filing Date

2024-07-18

Application No.

18776410

Claims

20

View original document →

Named provisions

Machine-learning driven data analysis based on demographics, risk, and need

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Last updated

Classification

Agency
USPTO
Published
April 14th, 2026
Instrument
Notice
Legal weight
Binding
Stage
Final
Change scope
Minor
Document ID
US12602730B2

Who this affects

Applies to
Technology companies Insurance companies Investors
Industry sector
5112 Software & Technology
Activity scope
Patent grants Machine learning systems Insurance technology
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Data Privacy Artificial Intelligence

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