Trust layer for generative artificial intelligence (ai) application

A non-transitory machine-readable storage medium that provides instructions that, if executed by a processor, are configurable to cause said processor to perform operations comprising:

• receiving a prompt from a user, by a large language model (LLM) gateway, via a user interface coupled with the LLM gateway;
• receiving, by the LLM gateway, a plurality of configuration parameters controlling at least one of:
• data privacy, trust based content moderation, regulatory compliance, and a business context specific to the user, in the prompt, the configuration parameters being transparent to the user;
• determining, by the LLM gateway, a presence of sensitive information in the prompt;
• in response to determining that sensitive information is present in the prompt, receiving, by the LLM gateway, a moderated version of the prompt comprising a moderated version of the sensitive information;
• receiving, by the LLM gateway, a response to the moderated version of the prompt;
• determining, by the LLM gateway, a presence of unsafe information in the response;
• in response to determining that unsafe information is present in the response, generating, by the LLM gateway, a safe version of the response comprising a moderated version of the unsafe information, in real-time, by controlling at least one of the configuration parameters;
• and
• sending, by the LLM gateway, the safe version of the response to the user.

A system comprising:

• a processor;
• a cloud-based computing resource digitally connected with the processor;
• a non-transitory machine-readable storage medium that provides instructions that, if executed by the processor, are configurable to cause the system to perform operations comprising:
• receiving a prompt from a user, by a large language model (LLM) gateway, via a user interface coupled with the LLM gateway;
• receiving, by the LLM gateway, a plurality of configuration parameters controlling at least one of:
• data privacy, trust based content moderation, regulatory compliance, and a business context specific to the user, in the prompt, the configuration parameters being transparent to the user;
• determining, by the LLM gateway, a presence of sensitive information in the prompt;
• in response to determining that sensitive information is present in the prompt, receiving, by the LLM gateway, a moderated version of the prompt comprising a moderated version of the sensitive information;
• receiving, by the LLM gateway, a response to the moderated version of the prompt;
• determining, by the LLM gateway, a presence of unsafe information in the response;
• in response to determining that unsafe information is present in the response, generating, by the LLM gateway, a safe version of the response comprising a moderated version of the unsafe information, in real-time, by controlling at least one of the configuration parameters;
• and
• sending, by the LLM gateway, the safe version of the response to the user.