| CPC G06Q 40/04 (2013.01) [G06F 16/215 (2019.01); G06F 16/2358 (2019.01); G06F 16/2379 (2019.01); G06F 16/275 (2019.01); G06Q 20/363 (2013.01); G06Q 20/3674 (2013.01); G06Q 20/3829 (2013.01); G06Q 20/389 (2013.01); G06Q 20/401 (2013.01); G06Q 20/42 (2013.01); G06Q 30/0613 (2013.01); G06Q 40/06 (2013.01); H04L 9/50 (2022.05); H04L 67/1097 (2013.01); G06Q 2220/00 (2013.01)] | 14 Claims |

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1. A computer-implemented method comprising:
electronically collecting a first data set, purportedly defining characteristics of the asset, into a database;
accessing unique identifiers corresponding to each of one or more items within the first data set;
formulating a JSON object containing the one or more items;
assigning an additional unique identifier to the asset;
creating a job on a queue containing the additional unique identifier and the JSON object; and
pinging an artificial intelligence module there is an object in the queue;
automatically and subsequent to accessing the unique identifiers, utilizing the artificial intelligence module validating relevancy of the one or more items to the asset, including:
sending out an asynchronous search for matches on the one or more items contained in the JSON object electronically collecting a second data set into the database using the unique identifiers, the second data set considered as corresponding to the asset based on the unique identifiers;
cross-referencing the first data set with the second data set; and
confirming relevancy of the one or more items to the asset based on results of the cross-referencing;
listing the asset at a financial exchange; and
automatically, as part of a constant training cycle, training the artificial intelligence module based on confirming the relevancy of the one or more items improving data validating performance of the artificial intelligence module.
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