Granted Patent B2

US 12,737,664 · App. 18/807,146 · Granted Sep 15, 2026

Inventors: George Albero (Charlotte, NC); Naga Vamsi Krishna Akkapeddi (Charlotte, NC); Sakshi Bakshi (New Delhi, IN)

Assignee: Bank of America Corporation

G06N10/70G06F21/6245G06F21/6254G06F21/6263G06F21/6281G06F21/629

Abstract

Claims (80)

1 . A computing platform comprising:

at least one processor;

a communication interface communicatively coupled to the at least one processor; and

memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

train, based on historical information, an artificial intelligence (AI) engine, wherein training the AI engine configures the AI engine to identify an action to resolve an error;

extract metadata from one or more interconnected enterprise processing systems;

use the metadata to map the one or more interconnected enterprise processing systems, wherein the mapping identifies one or more connections within the one or more interconnected enterprise processing systems between one or more of:

the one or more interconnected enterprise processing systems; or

applications within the one or more interconnected enterprise processing systems;

generate one or more dynamic markers;

create, using a quantum noise inducer and via laplace transformation, a pair of differential privacy components for each of the one or more dynamic markers, wherein each differential privacy component of the pair of differential privacy components is related to the other differential privacy component of the pair of differential privacy components via quantum entanglement such that an effect on one differential privacy component of the pair of differential privacy components impacts the other differential privacy component of the pair of differential privacy components;

store a first of the pair of differential privacy components at the computing platform;

inject a second of the pair of differential privacy components into the metadata of the one or more interconnected enterprise processing systems, wherein injecting the second of the pair of differential privacy components into the metadata causes the second of the pair of differential privacy components to appear as noise within the metadata;

detect that a dynamic marker has been activated, wherein the dynamic marker is activated by:

activating, at one of the one or more interconnected enterprise processing systems, the second of the pair of differential privacy components that corresponds to the dynamic marker;

activating, at the computing platform and based on the activating of the second of the pair of differential privacy components, the first of the pair of differential privacy components, wherein the first of the pair of differential privacy components and the second of the pair of differential privacy components correspond to the dynamic marker that was activated, and wherein the activating of the first of the pair of differential privacy components is based on the activating of the second of the pair of differential privacy components and the quantum entanglement of the pair of differential privacy components;

identify an error that corresponds to the dynamic marker that was activated;

identify an action based on the error using the AI engine; and

execute the action by sending commands to the one or more interconnected processing systems, that when received by the one or more interconnected processing systems, directs one of the one or more interconnected processing systems to execute the action.

2 . The computing platform of claim 1 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

generate a report, wherein the report comprises the error that corresponds to the dynamic marker that was activated, and the action that was executed.

3 . The computing platform of claim 2 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

send, to an enterprise user device, the report and one or more commands directing the enterprise user device to display the report, wherein sending the one or more commands directing the enterprise user device to display the report causes the enterprise user device to display the report.

4 . The computing platform of claim 1 , wherein the memory stores computer-readable instructions that, when executed by the at least one processor, further cause the computing platform to:

create one or more blueprints, wherein each of the one or more blueprints corresponds to one or more transactions within the one or more interconnected enterprise processing systems.

5 . The computing platform of claim 1 , wherein the historical information further comprises:

historical errors, historical actions that resolved corresponding historical errors, historical dynamic markers, and historical transactions.

6 . The computing platform of claim 1 , wherein the one or more dynamic markers comprise one or more of:

a transaction marker, an application marker, a system marker, a network marker, a hardware marker, or a software marker.

7 . The computing platform of claim 1 , wherein the creating is performed using differential privacy.

8 . The computing platform of claim 1 , wherein the memory stores computer-readable instructions that, when executed by the at least one processor, further cause the computing platform to:

update, using a dynamic feedback loop and based on the detecting, the identifying, and the executing, the AI engine.

9 . The computing platform of claim 1 , wherein the identifying the error that corresponds to the dynamic marker that was activated comprises automatically identifying the error using the AI engine.

10 . A method comprising:

at a computing platform comprising at least one processor, a communication interface, and memory:

training, based on historical information, an artificial intelligence (AI) engine, wherein training the AI engine configures the AI engine to identify an action to resolve an error;

extracting metadata from one or more interconnected enterprise processing systems;

using the metadata to map the one or more interconnected enterprise processing systems, wherein the mapping identifies one or more connections within the one or more interconnected enterprise processing systems between one or more of:

the one or more interconnected enterprise processing systems; or

applications within the one or more interconnected enterprise processing systems;

generating one or more dynamic markers;

creating, using a quantum noise inducer and via laplace transformation, a pair of differential privacy components for each of the one or more dynamic markers, wherein each differential privacy component of the pair of differential privacy components is related to the other differential privacy component of the pair of differential privacy components via quantum entanglement such that an effect on one differential privacy component of the pair of differential privacy components impacts the other differential privacy component of the pair of differential privacy components;

storing a first of the pair of differential privacy components at the computing platform;

injecting a second of the pair of differential privacy components into the metadata of the one or more interconnected enterprise processing systems, wherein injecting the second of the pair of differential privacy components into the metadata causes the second of the pair of differential privacy components to appear as noise within the metadata;

detecting that a dynamic marker has been activated, wherein the dynamic marker is activated by:

activating, at one of the one or more interconnected enterprise processing systems, the second of the pair of differential privacy components that corresponds to the dynamic marker;

activating, at the computing platform and based on the activating of the second of the pair of differential privacy components, the first of the pair of differential privacy components, wherein the first of the pair of differential privacy components and the second of the pair of differential privacy components correspond to the dynamic marker that was activated, and wherein the activating of the first of the pair of differential privacy components is based on the activating of the second of the pair of differential privacy components;

identifying an error that corresponds to the dynamic marker that was activated;

identifying an action based on the error using the AI engine; and

executing the action by sending commands to the one or more interconnected processing systems, that when received by the one or more interconnected processing systems, directs one of the one or more interconnected processing systems to execute the action.

11 . The method of claim 10 , further comprising:

generating a report, wherein the report comprises the error that corresponds to the dynamic marker that was activated, and the action that was executed.

12 . The method of claim 11 , further comprising:

sending, to an enterprise user device, the report and one or more commands directing the enterprise user device to display the report, wherein sending the one or more commands directing the enterprise user device to display the report causes the enterprise user device to display the report.

13 . The method of claim 10 , further comprising:

creating one or more blueprints, wherein each of the one or more blueprints corresponds to one or more transactions within the one or more interconnected enterprise processing systems.

14 . The method of claim 10 , wherein the historical information further comprises:

historical errors, historical actions that resolved corresponding historical errors, historical dynamic markers, and historical transactions.

15 . The method of claim 10 , wherein the one or more dynamic markers comprise one or more of:

a transaction marker, an application marker, a system marker, a network marker, a hardware marker, or a software marker.

16 . The method of claim 10 , wherein the creating is performed using differential privacy.

17 . The method of claim 10 , further comprising:

updating, using a dynamic feedback loop and based on the detecting, the identifying, and the executing, the AI engine.

18 . The method of claim 10 , wherein the identifying the error that corresponds to the dynamic marker that was activated comprises automatically identifying the error using the AI engine.

19 . One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

train, based on historical information, an artificial intelligence (AI) engine, wherein training the AI engine configures the AI engine to identify an action to resolve an error;

extract metadata from one or more interconnected enterprise processing systems;

use the metadata to map the one or more interconnected enterprise processing systems, wherein the mapping identifies one or more connections within the one or more interconnected enterprise processing systems between one or more of:

the one or more interconnected enterprise processing systems; or

applications within the one or more interconnected enterprise processing systems;

generate one or more dynamic markers;

create, using a quantum noise inducer and via laplace transformation, a pair of differential privacy components for each of the one or more dynamic markers, wherein each differential privacy component of the pair of differential privacy components is related to the other differential privacy component of the pair of differential privacy components via quantum entanglement such that an effect on one differential privacy component of the pair of differential privacy components impacts the other differential privacy component of the pair of differential privacy components;

store a first of the pair of differential privacy components at the computing platform;

inject a second of the pair of differential privacy components into the metadata of the one or more interconnected enterprise processing systems, wherein injecting the second of the pair of differential privacy components into the metadata causes the second of the pair of differential privacy components to appear as noise within the metadata;

detect that a dynamic marker has been activated, wherein the dynamic marker is activated by:

activating, at one of the one or more interconnected enterprise processing systems, the second of the pair of differential privacy components that corresponds to the dynamic marker;

activating, at the computing platform and based on the activating of the second of the pair of differential privacy components, the first of the pair of differential privacy components, wherein the first of the pair of differential privacy components and the second of the pair of differential privacy components correspond to the dynamic marker that was activated, and wherein the activating of the first of the pair of differential privacy components is based on the activating of the second of the pair of differential privacy components;

identify an error that corresponds to the dynamic marker that was activated;

identify an action based on the error using the AI engine; and

execute the action by sending commands to the one or more interconnected processing systems, that when received by the one or more interconnected processing systems, directs one of the one or more interconnected processing systems to execute the action.

Assignments (1)

Continuity (1)

References Cited (36)