Validating generative artificial intelligence output

An apparatus for analyzing a generative artificial intelligence (AI) model, comprising:

• one or more memories storing processor-executable code;
• and
• one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the apparatus to:
• train the generative AI model on a plurality of data sources;
• generate, based at least in part on the training, training log metadata indicating individual data sources of the plurality of data sources;
• receive, from a user device, a generative AI query;
• generate, using the trained generative AI model and based at least in part on one or more data sources of the plurality of data sources, a response to the generative AI query;
• perform a first natural language analysis to tokenize information of the one or more data sources and generate a plurality of data source tokens;
• perform a second natural language analysis to tokenize contents of the response and generate a plurality of response tokens;
• map individual data source tokens of the plurality of data source tokens to individual response tokens of the plurality of response tokens;
• map, based at least in part on the mapping of the individual data source tokens to the individual response tokens, one or more portions of the response to the one or more data sources of the plurality of data sources based at least in part on the training log metadata;
• and
• transmit, to the user device, the response and one or more indications of the one or more data sources based at least in part on the mapping and the training log metadata.

A non-transitory computer-readable medium storing code for analyzing a generative artificial intelligence (AI) model, the code comprising instructions executable by one or more processors to:

• train the generative AI model on a plurality of data sources;
• generate, based at least in part on the training, training log metadata indicating individual data sources of the plurality of data sources;
• receive, from a user device, a generative AI query;
• generate, using the trained generative AI model and based at least in part on one or more data sources of the plurality of data sources, a response to the generative AI query;
• perform a first natural language analysis to tokenize information of the one or more data sources and generate a plurality of data source tokens;
• perform a second natural language analysis to tokenize contents of the response and generate a plurality of response tokens;
• map individual data source tokens of the plurality of data source tokens to individual response tokens of the plurality of response tokens;
• map, based at least in part on the mapping of the individual data source tokens to the individual response tokens, one or more portions of the response to the one or more data sources of the plurality of data sources based at least in part on the training log metadata;
• and
• transmit, to the user device, the response and one or more indications of the one or more data sources based at least in part on the mapping and the training log metadata.