Granted Patent B2

US 12,748,827 · App. 18/951,120 · Granted Sep 29, 2026

Inventors: 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)

G06F21/31G06F21/6218G06F40/20

Abstract

Claims (103)

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

receive an output generation request comprising an input for generation of an output using a first artificial intelligence (AI) model;

provide the output generation request to a first input validation model to modify the input,

wherein modifying the input comprises:

determining that the input includes a forbidden token; and

generating the modified input by omitting the forbidden token;

determine a performance metric value associated with the output generation request,

wherein the performance metric value indicates a requirement for the output generation request;

compare the performance metric value of the output generation request with a first performance criterion associated with the first AI model of a plurality of AI models;

in response to determining that the performance metric value satisfies the first performance criterion, provide the modified input to the first AI model to generate the output; and

enable access to the output by a user.

2 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions further cause the system to:

determine a user identifier associated with the user;

determine, from a token database, a stored token associated with the user identifier;

compare the stored token and an authentication token associated with the output generation request; and

in response to determining that the stored token and the authentication token associated with the output generation request match, authenticate the user.

3 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions further cause the system to:

generate, based on the output generation request, an event record including (1) the performance metric value, (2) a user identifier associated with the user, and (3) the input; and

transmit, to a server system, the event record for storage in an event database.

4 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions for modifying the input cause the system to:

determine that the input includes a first alphanumeric token;

determine that one or more records in a sensitive token database include a representation of the first alphanumeric token; and

modify the input to include a second alphanumeric token in lieu of the first alphanumeric token,

wherein the sensitive token database does not include a record representing the second alphanumeric token.

5 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions for modifying the input cause the system to:

generate a trace token comprising a traceable alphanumeric token; and

generate the modified input to include the trace token.

6 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions for comparing the performance metric value with the first performance criterion cause the system to:

generate a cost metric value associated with the requirement for the output generation request;

determine a threshold cost associated with the first AI model; and

determine that the cost metric value satisfies the threshold cost.

7 . The non-transitory computer-readable storage medium of claim 1 , wherein the instructions further cause the system to:

extract a code sample from the output, wherein the code sample includes code for a software routine;

compile, within a virtual machine of the system, the code sample to generate an executable program associated with the software routine;

execute, within the virtual machine, the software routine using the executable program;

detect an anomaly in the execution of the software routine;

in response to detecting the anomaly in the execution of the software routine, generate a validation indicator to include an indication of the anomaly; and

in response to generating the validation indicator, enable access to the output by the user.

8 . A system comprising:

at least one hardware processor; and

at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the system to:

receive an output generation request comprising an input for generation of an output using a first AI model;

provide the output generation request to a first input validation model to modify the input,

wherein modifying the input comprises:

generating a traceable token; and

generating the modified input to include the traceable token;

determine a performance metric value associated with the output generation request,

wherein the performance metric value indicates a requirement for the output generation request;

compare the performance metric value of the output generation request with a first performance criterion associated with the first AI model of a plurality of AI models;

in response to determining that the performance metric value satisfies the first performance criterion, provide the modified input to the first AI model to generate the output; and

enable access to the output by a user.

9 . The system of claim 8 , wherein the instructions further cause the system to:

determine a user identifier associated with the user;

determine, from a token database, a stored token associated with the user identifier;

compare the stored token and an authentication token associated with the output generation request; and

in response to determining that the stored token and the authentication token associated with the output generation request match, authenticate the user.

10 . The system of claim 8 , wherein the instructions further cause the system to:

generate, based on the output generation request, an event record including (1) the performance metric value, (2) a user identifier associated with the user, and (3) the input; and

transmit, to a server system, the event record for storage in an event database.

11 . The system of claim 8 , wherein the instructions for modifying the input cause the system to:

determine that the input includes a first alphanumeric token;

determine that one or more records in a sensitive token database include a representation of the first alphanumeric token; and

modify the input to include a second alphanumeric token in lieu of the first alphanumeric token,

wherein the sensitive token database does not include a record representing the second alphanumeric token.

12 . The system of claim 8 , wherein the instructions for modifying the input cause the system to:

determine that the input includes a forbidden token; and

generate the modified input by omitting the forbidden token.

13 . The system of claim 8 , wherein the instructions for comparing the performance metric value with the first performance criterion cause the system to:

generate a cost metric value associated with the requirement for the output generation request;

determine a threshold cost associated with the first AI model; and

determine that the cost metric value satisfies the threshold cost.

14 . The system of claim 8 , wherein the instructions for providing the output generation request to the first input validation model cause the system to:

identify an attribute of the output generation request;

determine, based on the attribute, the first input validation model of a plurality of prompt validation models; and

provide the output generation request to the first input validation model.

15 . A method comprising:

receiving an output generation request comprising an input for generation of an output using a first AI model of a plurality of AI models;

modifying, using a first input validation model, the output generation request by modifying the input to omit a set of forbidden tokens;

determining a performance metric value associated with the modified output generation request,

wherein the performance metric value indicates a requirement for the modified output generation request;

comparing the performance metric value of the modified output generation request with a first performance criterion associated with the first AI model; and

in response to determining that the performance metric value satisfies the first performance criterion, enabling access to the output by a user.

16 . The method of claim 15 , further comprising:

determining a user identifier associated with the user;

determining, from a token database, a stored token associated with the user identifier;

comparing the stored token and an authentication token associated with the output generation request; and

in response to determining that the stored token and the authentication token associated with the output generation request match, authenticating the user.

17 . The method of claim 15 , comprising:

generating, based on the output generation request, an event record including (1) the performance metric value, (2) a user identifier associated with the user, and (3) the input; and

transmitting, to a server system, the event record for storage in an event database.

18 . The method of claim 15 , comprising:

determining that the input includes a first alphanumeric token;

determining that one or more records in a sensitive token database include a representation of the first alphanumeric token; and

modifying the input to include a second alphanumeric token in lieu of the first alphanumeric token,

wherein the sensitive token database does not include a record representing the second alphanumeric token.

19 . The method of claim 15 , wherein comparing the performance metric value with the first performance criterion comprises:

generating a cost metric value associated with the requirement for the output generation request;

determining a threshold cost associated with the first AI model; and

determining that the cost metric value satisfies the threshold cost.

20 . The method of claim 15 , wherein providing the output generation request to the first input validation model comprises:

identifying an attribute of the output generation request;

determining, based on the attribute, the first input validation model of a plurality of prompt validation models; and

providing the output generation request to the first input validation model.

Assignments (1)

Continuity (2)

References Cited (189)