Artificial intelligence for compliance simplification in cross-border logistics

A computer-implemented method for inferring information about a product, comprising:

• feeding a product data record corresponding to at least a first product into one or more machine learning (ML) models to identify at least one predictive attribute that corresponds to product information not included in the product data record,
• wherein the predictive attribute corresponds to product data needed to ship the first product to a first destination;
• feeding the product data record and the predictive attribute, corresponding to product data needed to ship the first product to the first destination, into the one or more machine learning models to estimate additional data for one or more null fields in the product data record,
• wherein the null fields correspond to data needed to generate compliant shipping information, and
• wherein the additional data comprises data needed to generate compliant shipping information;
• updating the product data record with the estimated additional data comprising data needed to generate compliant shipping information;
• and
• predicting product code data by feeding the updated product data record including the data needed to generate compliant shipping information, into an ensemble of one or more ML models, the product code data based on one or more commerce classification code taxonomies.

A system comprising:

• one or more processors;
• and
• a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:
• feed a product data record, corresponding to at least the first product, into one or more machine learning (ML) models to identify at least one predictive attribute that corresponds to product information not included in the product data record,
• wherein the predictive attribute corresponds to product data needed to ship the first product to a first destination;
• feed the product data record, corresponding to at least the first product, and the predictive attribute, corresponding to product data needed to ship the first product to the first destination, into the one or more machine learning models to estimate additional data for one or more null fields in the product data record, corresponding to at least the first product,
• wherein the null fields correspond to data needed to generate compliant shipping information, and
• wherein the additional data comprises data needed to generate compliant shipping information;
• update the product data record, corresponding to at least the first product, with the estimated additional data comprising data needed to generate compliant shipping information;
• and
• predict product code data by feeding the updated product data record into an ensemble of one or more ML models, the product code data based on one or more commerce classification code taxonomies.