IP Library Granted Patent US 12,524,809
Granted Patent B1
US 12,524,809 · App. 18/963,062 · Granted Jan 13, 2026

Evaluating tokenized entities using an artificial intelligence (AI) model

Inventors: Brandon Krull (Santa Ana, CA); Syed M. Amir Husain (Georgetown, TX); Steven Lau (Westport, CT); Thiam Hui Lee (New York, NY); Aldo Marini Macouzet (Alameda, CA)
Assignee: ALPHA DEAL LLC
G06Q40/04
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Quick Facts
Patent No.
US 12,524,809
App. No.
18/963,062
Granted
Jan 13, 2026
Kind
B1
Abstract

Methods, apparatuses, system, devices, and computer program products for evaluating tokenized entities using an AI model are disclosed. In a particular embodiment, a controller generates a profile for a digitally traded asset and generates, using an AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset. The controller stores the profile for a digitally traded asset and the one or more entity profiles in a database comprising a plurality of entity profiles corresponding to different entities. The controller augments the AI model based on the plurality of entity profiles. The controller generates using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles.

Claims (73)

1 . A method of evaluating tokenized entities using an artificial intelligence (AI) model, the method comprising:

generating, by a controller, a profile for a digitally traded asset;

generating, by the controller using an AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset including for each entity of the one or more entities:

using an AI model to architect search queries and natural language search strings associated with the entity;

based on the architected search queries and natural language search strings, performing a web scraping operation on unstructured data sources to retrieve and aggregate unstructured external data related to the entity;

using the AI model to transform the retrieved unstructured external data into structured data; and

entering within an entity database, the structured data into an entity profile of a plurality of entity profiles, the entity profile associated with the entity;

storing the profile for a digitally traded asset and the one or more entity profiles in a database comprising a plurality of entity profiles corresponding to different entities;

configuring and augmenting, by the controller, the AI model to focus on analyzing data sets relevant to the one or more entity profiles in the database by performing retrieval-augmented generation based on the one or more entity profiles to generate input for the augmented AI model;

generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles; and

outputting, by the controller, the rating for the digitally traded asset to a user.

2 . The method of claim 1 , wherein the digitally traded asset is a token.

3 . The method of claim 2 , wherein the token represents a share of ownership in a fund; and wherein the fund holds a security in each of the one or more entities.

4 . The method of claim 1 , wherein the rating includes one or more of a valuation analysis, a risk assessment, a score, and a rank.

5 . The method of claim 1 , wherein generating, by the controller using the AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset includes iteratively:

retrieving, by the controller, data related to an entity, the data including structured data and unstructured data;

determining, by applying the retrieved data to an AI model, a structure for the unstructured data, the structure including a plurality of fields; and

populating one or more fields of an entity profile with a respective value that is extracted from the retrieved data using the AI model.

6 . The method of claim 1 , wherein configuring and augmenting, by the controller, the AI model includes:

extracting, by the controller, time-series valuation data from the plurality of entity profiles in the database; and

augmenting, by the controller, the AI model based on the extracted time-series valuation; and

wherein generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles includes:

generating, by the controller using the augmented AI model, a valuation analysis of the digitally traded asset.

7 . The method of claim 6 , wherein generating, by the controller using the augmented AI model, a valuation analysis of the digitally traded asset includes:

generating, by the controller using the augmented AI model, a valuation analysis of each of the one or more entities backing the digitally traded asset.

8 . The method of claim 1 , wherein generating, by the controller using the AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles includes:

generating, by the controller using the AI model, a score for each of the one or more entities that back the digitally traded asset.

9 . The method of claim 1 further comprising:

adjusting activation weights of the AI model based on user information indicating a user preference.

10 . An apparatus for evaluating tokenized entities using an artificial intelligence (AI) model, the apparatus comprising:

a processor;

one or more computer-readable storage media coupled to the processor; and

program instructions stored on the one or more storage media to cause the processor to perform operations comprising:

generating, by a controller, a profile for a digitally traded asset;

generating, by the controller using an AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset including for each entity of the one or more entities:

using an AI model to architect search queries and natural language search strings associated with the entity;

based on the architected search queries and natural language search strings, performing a web scraping operation on unstructured data sources to retrieve and aggregate unstructured external data related to the entity;

using the AI model to transform the retrieved unstructured external data into structured data; and

entering within an entity database, the structured data into an entity profile of a plurality of entity profiles, the entity profile associated with the entity:

storing the profile for a digitally traded asset and the one or more entity profiles in a database comprising a plurality of entity profiles corresponding to different entities;

configuring and augmenting, by the controller, the AI model to focus on analyzing data sets relevant to the one or more entity profiles in the database by performing retrieval-augmented generation based on the one or more entity profiles to generate input for the augmented AI model;

generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles; and

outputting, by the controller, the rating for the digitally traded asset to a user.

11 . The apparatus of claim 10 , wherein the digitally traded asset is a token.

12 . The apparatus of claim 11 , wherein the token represents a share of ownership in a fund; and wherein the fund holds a security in each of the one or more entities.

13 . The apparatus of claim 10 , wherein the rating includes one or more of a valuation analysis, a risk assessment, a score, and a rank.

14 . The apparatus of claim 10 , wherein configuring and augmenting, by the controller, the AI model includes:

extracting, by the controller, time-series valuation data from the plurality of entity profiles in the database; and

augmenting, by the controller, the AI model based on the extracted time-series valuation; and

wherein generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles includes:

generating, by the controller using the augmented AI model, a valuation analysis of the digitally traded asset.

15 . A computer program product for evaluating tokenized entities using an artificial intelligence (AI) model, the computer program product comprising:

a set of one or more computer readable storage media; and

computer program instructions, collectively stored in the set of one or more storage media, that when executed, cause a processor to perform computer operations comprising:

generating, by a controller, a profile for a digitally traded asset;

generating, by the controller using an AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset including for each entity of the one or more entities:

using an AI model to architect search queries and natural language search strings associated with the entity;

based on the architected search queries and natural language search strings, performing a web scraping operation on unstructured data sources to retrieve and aggregate unstructured external data related to the entity;

using the AI model to transform the retrieved unstructured external data into structured data; and

entering within an entity database, the structured data into an entity profile of a plurality of entity profiles, the entity profile associated with the entity;

storing the profile for a digitally traded asset and the one or more entity profiles in a database comprising a plurality of entity profiles corresponding to different entities; and

configuring and augmenting, by the controller, the AI model to focus on analyzing data sets relevant to the one or more entity profiles in the database by performing retrieval-augmented generation based on the one or more entity profiles to generate input for the augmented AI model;

generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles; and

outputting, by the controller, the rating for the digitally traded asset to a user.

16 . The computer program product of claim 15 , wherein the digitally traded asset is a token.

17 . The computer program product of claim 16 , wherein the token represents a share of ownership in a fund; and wherein the fund holds a security in each of the one or more entities.

18 . The computer program product of claim 15 , wherein configuring and augmenting, by the controller, the AI model includes:

extracting, by the controller, time-series valuation data from the plurality of entity profiles in the database; and

augmenting, by the controller, the AI model based on the extracted time-series valuation; and

wherein generating, by the controller using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles includes:

generating, by the controller using the augmented AI model, a valuation analysis of the digitally traded asset.

19 . The computer program product of claim 15 , wherein generating, by the controller using the AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles includes:

generating, by the controller using the AI model, a score for each of the one or more entities that back the digitally traded asset.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 3, 2025
From: KRULL, BRANDON; HUSAIN, SYED M. AMIR; LAU, STEVEN; LEE, THIAM HUI; MACOUZET, ALDO MARINI
To: ALPHA DEAL LLC
Reel/Frame 070384/0410 →
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