Granted Patent B2

US 12,524,508 · App. 19/188,116 · Granted Jan 13, 2026

Inventors: Nigil Satish Jeyashekar (Irving, TX); Jason Engelbrecht (London, GB); Zheyu Wang (Shanghai, CN); Haolin Jin (Shanghai, CN); Payal Jain (London, GB); Tariq Husayn Maonah (London, GB); Mariusz Saternus (Cracow, PL); Daniel Lewandowski (Cracow, PL); Biraj Krushna Rath (London, GB); Stuart Murray (London, GB); Philip Davies (London, GB); Sourabh Deb (Tampa, FL)

G06F21/31G06F21/6218G06F40/20

Abstract

Claims (79)

1 . One or more non-transitory, computer-readable storage media comprising instructions recorded thereon, wherein the instructions, when executed by at least one data processor of a system, cause the system to:

receive a user prompt indicating a request for a report summarizing data over a time period;

generate a first output by inputting, into a generative model, the user prompt to cause the generative model to generate the first output based on the user prompt, the first output comprising a first plurality of text-based analytics, a first plurality of visual analytics, and a first plurality of queries;

generate a second output by causing the system to:

retrieve, from a database associated with the data requested in the user prompt, a rule-based pseudocode;

generate a pseudocode prompt based on the rule-based pseudocode and the data requested in the user prompt; and

input, into the generative model, the pseudocode prompt to cause the generative model to generate the second output based on the pseudocode prompt, the second output comprising a second plurality of text-based analytics, a second plurality of visual analytics, and a second plurality of queries;

perform a comparison between (i) the first plurality of text-based analytics and the second plurality of text-based analytics, (ii) the first plurality of visual analytics and the second plurality of visual analytics, and (iii) the first plurality of queries and the second plurality of queries, to determine a match accuracy between the first output and the second output;

determine whether the match accuracy satisfies an accuracy threshold;

based on the match accuracy failing to satisfy the accuracy threshold, generate a restructured prompt based on the user prompt and the rule-based pseudocode; and

approve the restructured prompt for use in conjunction with the generative model.

2 . The one or more non-transitory, computer-readable storage media of claim 1 , wherein, to approve the restructured prompt, the instructions further cause the system to:

generate an updated first output by inputting, into the generative model, the restructured prompt to cause the generative model to generate the updated first output based on the restructured prompt, the updated first output comprising an updated first plurality of text-based analytics, an updated first plurality of visual analytics, and an updated first plurality of queries;

perform an updated comparison of the updated first output and the second output to determine an updated match accuracy;

determine whether the updated match accuracy satisfies the accuracy threshold; and

based on the updated match accuracy satisfying the accuracy threshold, approve the restructured prompt.

3 . The one or more non-transitory, computer-readable storage media of claim 2 , wherein performing the updated comparison comprises causing the system to compare (i) the updated first plurality of text-based analytics with the second plurality of text-based analytics, (ii) the updated first plurality of visual analytics with the second plurality of visual analytics, and (iii) the updated first plurality of queries with the second plurality of queries.

4 . The one or more non-transitory, computer-readable storage media of claim 1 , wherein performing the comparison comprises causing the system to determine a measure of similarity between (i) the first plurality of text-based analytics and the second plurality of text-based analytics, (ii) the first plurality of visual analytics and the second plurality of visual analytics, and (iii) the first plurality of queries and the second plurality of queries.

5 . The one or more non-transitory, computer-readable storage media of claim 1 , wherein the instructions further cause the system to:

determine a ranking of categories of the first output and the second output according to a measure of importance of each category, the categories comprising text-based analytics, visual analytics, and queries,

wherein the comparison is performed according to the ranking.

6 . The one or more non-transitory, computer-readable storage media of claim 5 , wherein, to perform the comparison according to the ranking, the instructions further cause the system to:

compare a higher-ranked category between the first output and the second output, wherein the categories of the first output and the second output comprise at least a higher-ranked category and a lower-ranked category;

based on determining that the higher-ranked category fails to match between the first output and the second output, generate the restructured prompt; and

based on determining that the higher-ranked category matches between the first output and the second output, approve the user prompt.

7 . A method comprising:

receiving a user prompt indicating a request for data over a time period;

generating a first output by inputting, into a generative model, the user prompt to cause the generative model to generate the first output based on the user prompt, the first output comprising a first plurality of text-based analytics, a first plurality of visual analytics, and a first plurality of queries;

generating a second output by:

retrieving, from a database associated with the data requested in the user prompt, a structured pseudocode;

generating a pseudocode prompt based on the structured pseudocode and the data requested in the user prompt; and

inputting, into the generative model, the pseudocode prompt to cause the generative model to generate the second output based on the pseudocode prompt, the second output comprising a second plurality of text-based analytics, a second plurality of visual analytics, and a second plurality of queries;

performing a comparison of the first output and the second output; and

based on the comparison indicating that the first output does not match the second output, generating a restructured prompt based on the user prompt and the structured pseudocode.

8 . The method of claim 7 , wherein performing the comparison further comprises:

determining, based on the comparison, a match accuracy between the first output and the second output; and

determining whether the match accuracy satisfies an accuracy threshold,

wherein the restructured prompt is generated based on the comparison indicating that the match accuracy does not satisfy the accuracy threshold.

9 . The method of claim 8 , further comprising:

generating an updated first output by inputting, into the generative model, the restructured prompt to cause the generative model to generate the updated first output based on the restructured prompt, the updated first output comprising an updated first plurality of text-based analytics, an updated first plurality of visual analytics, and an updated first plurality of queries;

performing an updated comparison of the updated first output and the second output to determine an updated match accuracy;

determining whether the updated match accuracy satisfies the accuracy threshold; and

based on the updated match accuracy satisfying the accuracy threshold, approving the restructured prompt.

10 . The method of claim 9 , wherein performing the updated comparison comprises comparing (i) the updated first plurality of text-based analytics with the second plurality of text-based analytics, (ii) the updated first plurality of visual analytics with the second plurality of visual analytics, and (iii) the updated first plurality of queries with the second plurality of queries.

11 . The method of claim 7 , wherein performing the comparison comprises comparing (i) the first plurality of text-based analytics with the second plurality of text-based analytics, (ii) the first plurality of visual analytics with the second plurality of visual analytics, and (iii) the first plurality of queries with the second plurality of queries.

12 . The method of claim 7 , further comprising:

determining a ranking of categories of the first output and the second output according to a measure of importance of each category, the categories comprising text-based analytics, visual analytics, and queries,

wherein the comparison is performed according to the ranking.

13 . The method of claim 12 , wherein performing the comparison according to the ranking comprises:

comparing a higher-ranked category between the first output and the second output, wherein the categories of the first output and the second output comprise at least a higher-ranked category and a lower-ranked category;

based on determining that the higher-ranked category fails to match between the first output and the second output, generating the restructured prompt; and

based on determining that the higher-ranked category matches between the first output and the second output, approving the user prompt.

14 . A system comprising:

a storage device; and

one or more processors communicatively coupled to the storage device storing instructions thereon that cause the one or more processors to:

receive a prompt indicating a request for data over a time period;

generate a first output by inputting, into a machine learning model, the prompt to cause the machine learning model to generate the first output based on the prompt;

generate a second output by causing the one or more processors to:

generate a pseudocode prompt based on a structured pseudocode and the data requested in the prompt; and

input, into the machine learning model, the pseudocode prompt to cause the machine learning model to generate the second output based on the pseudocode prompt;

perform a comparison of the first output and the second output; and

based on the comparison, generate a restructured prompt based on the prompt and the structured pseudocode.

15 . The system of claim 14 , wherein, to perform the comparison, the instructions further cause the one or more processors to:

determine, based on the comparison, a match accuracy between the first output and the second output; and

determine whether the match accuracy satisfies an accuracy threshold, wherein the restructured prompt is generated based on the comparison indicating that the match accuracy does not satisfy the accuracy threshold.

16 . The system of claim 15 , wherein the instructions further cause the one or more processors to:

generate an updated first output by inputting, into the machine learning model, the restructured prompt to cause the machine learning model to generate the updated first output based on the restructured prompt, the updated first output comprising an updated first plurality of text-based analytics, an updated first plurality of visual analytics, and an updated first plurality of queries;

perform an updated comparison of the updated first output and the second output to determine an updated match accuracy;

determine whether the updated match accuracy satisfies the accuracy threshold; and

based on the updated match accuracy satisfying the accuracy threshold, approve the restructured prompt.

17 . The system of claim 16 , wherein the second output comprises a second plurality of text-based analytics, a second plurality of visual analytics, and a second plurality of queries, and wherein performing the updated comparison comprises causing the one or more processors to compare (i) the updated first plurality of text-based analytics with the second plurality of text-based analytics, (ii) the updated first plurality of visual analytics with the second plurality of visual analytics, and (iii) the updated first plurality of queries with the second plurality of queries.

18 . The system of claim 14 , wherein the first output comprises a first plurality of text-based analytics, a first plurality of visual analytics, and a first plurality of queries, wherein the second output comprises a second plurality of text-based analytics, a second plurality of visual analytics, and a second plurality of queries, and wherein performing the comparison comprises causing the one or more processors to compare (i) the first plurality of text-based analytics with the second plurality of text-based analytics, (ii) the first plurality of visual analytics with the second plurality of visual analytics, and (iii) the first plurality of queries with the second plurality of queries.

19 . The system of claim 14 , wherein the instructions further cause the one or more processors to:

determine a ranking of categories of the first output and the second output according to a measure of importance of each category, the categories comprising text-based analytics, visual analytics, and queries,

wherein the comparison is performed according to the ranking.

20 . The system of claim 19 , wherein, to perform the comparison according to the ranking, the instructions further cause the one or more processors to:

compare a higher-ranked category between the first output and the second output, wherein the categories of the first output and the second output comprise at least a higher-ranked category and a lower-ranked category;

based on determining that the higher-ranked category fails to match between the first output and the second output, generate the restructured prompt; and

based on determining that the higher-ranked category matches between the first output and the second output, approve the prompt.

Assignments (2)

Continuity (10)

References Cited (147)