Systems and methods for automated exit verification

A method for store exit verification, comprising:

• capturing, in real-time and as a customer approaches an exit, a set of images of one or more items;
• constructing, via a computer vision engine, a preliminary item catalog based on the one or more items detected near the exit;
• constructing, via a machine learning engine and based on the preliminary item catalog, a refined item catalog by cross-referencing attributes of the one or more items against at least one of synthetic data, historical purchase patterns, contextual product groupings, and known inventory information;
• and
• detecting, via a verification engine and in real-time, discrepancies between the refined item catalog and a corresponding transaction log obtained from a transaction database, wherein the customer is allowed to pass through the exit based on the discrepancies.

A system for store exit verification, comprising:

• one or more point of sale units configured to construct a transaction log based on a transaction by a customer and output the transaction log to a transaction database;
• one or more sensing devices configured to, in real-time and as a customer approaches an exit, capture images of one or more items near the exit;
• a primary unit having one or more processors coupled to a memory having computer-readable instructions stored thereon, the primary unit comprising:
• a computer vision engine communicatively coupled to the one or more sensing devices, the computer vision engine configured to construct a preliminary item catalog based the on one or more items;
• a machine learning engine communicatively coupled to the computer vision engine and having one or more machine learning models, the one or more machine learning models trained to construct, based on the preliminary item catalog, a refined item catalog by cross-referencing attributes of the one or more items against at least one of synthetic data, historical purchase patterns, contextual product groupings, and known inventory information;
• and
• a verification engine communicatively coupled to the machine learning engine and a transaction database, the verification engine configured to detect, in real-time, discrepancies between the refined item catalog and the transaction log obtained from the transaction database, wherein the customer is allowed to pass through the exit based on the discrepancies;
• and
• a device communicatively coupled to the verification engine and having a user-interface configured to enable a user to view informatics based on the discrepancies.