Systems and methods for protecting proprietary data while using third-party ai/ml services
AssigneeLNRS Data Services Inc.
InventorKevin Hightower
Life of this patent
Estimating the term…
Abstract
Systems and methods are provided for utilizing AI/ML services to solve business problems while protecting proprietary information. Third-party AI/ML services are utilized in a multi-stage approach to answer a question and/or or solve a problem, create code to validate the answer, execute that code inside a proprietary system, and then use that answer to create a better answer without exposing proprietary data to a third-party.
Claims20
A method for utilizing AI/ML services to solve business problems while protecting proprietary information, comprising:
- identifying a question to be answered;
- formulating a prompt based on the question;
- submitting the prompt to a third-party AI/ML service;
- receiving an initial answer to the question based on the submitted prompt;
- validating the initial answer against data in a proprietary system;
- reformulating a validated initial answer into a coding question;
- submitting the coding question to the third-party AI/ML;
- receiving, from the third-party AI/ML service, a coding response to the coding question;
- executing the coding response in the proprietary system to generate a proprietary response;
- validating the proprietary response for one or more of security, privacy, performance, and accuracy against data in the proprietary system;
- creating a reformulated prompt based on the question and a validated proprietary response;
- submitting the reformulated prompt to the third-party AI/ML service;
- receiving final results from the third-party AI/ML service;
- and
- validating the final results based on predetermined criteria.
A system comprising:
- one or more processors;
- memory in communication with the one or more processors;
- instructions stored in the memory that, when executed by the one or more processors, cause the system to perform a method comprising:
- identifying a question to be answered;
- formulating a prompt based on the question;
- submitting the prompt to a third-party AI/ML service;
- receiving an initial answer to the question based on the submitted prompt;
- validating the initial answer against data in a proprietary system;
- reformulating a validated initial answer into a coding question;
- submitting the coding question to the third-party AI/ML;
- receiving, from the third-party AI/ML service, a coding response to the coding question;
- executing the coding response in the proprietary system to generate a proprietary response;
- validating the proprietary response for one or more of security, privacy, performance, and accuracy against data in the proprietary system;
- creating a reformulated prompt based on the question and a validated proprietary response;
- submitting the reformulated prompt to the third-party AI/ML service;
- receiving final results from the third-party AI/ML service;
- and
- validating the final results based on predetermined criteria.
At least one non-transitory computer-readable medium comprising a set of instructions that, in response to being executed by a processor circuit, cause the processor circuit to perform a method of:
- identifying a question to be answered;
- formulating a prompt based on the question;
- submitting the prompt to a third-party AI/ML service;
- receiving an initial answer to the question based on the submitted prompt;
- validating the initial answer against data in a proprietary system;
- reformulating a validated initial answer into a coding question;
- submitting the coding question to the third-party AI/ML;
- receiving, from the third-party AI/ML service, a coding response to the coding question;
- executing the coding response in the proprietary system to generate a proprietary response;
- validating the proprietary response for one or more of security, privacy, performance, and accuracy against data in the proprietary system;
- creating a reformulated prompt based on the question and a validated proprietary response;
- submitting the reformulated prompt to the third-party AI/ML service;
- receiving final results from the third-party AI/ML service;
- and
- validating the final results based on predetermined criteria.
Dependencies are inferred from the claim text.