Systems and methods for classifying documents

A system comprising:

• one or more processors;
• and
• a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:
• receive a first single-page document;
• iteratively, until a document type is identified:
• scan a portion of the first single-page document, wherein the portion is a fraction of the first single-page document;
• extract first data from the portion of the first single-page document;
• and
• determine whether the document type is identified by, using a machine learning model (MLM), determining whether the first data corresponds to one or more document types of a plurality of document types based on one or more confidence thresholds, wherein the portion of the first single-page document scanned increases by a predetermined amount each iteration, the predetermined amount being dynamically updated each iteration by:
• determining that a predefined amount of empty space is identified within the portion of the first single-page document;
• responsive to determining the predefined amount of empty space is identified within the portion of the first single-page document, increasing the portion of the first single-page document scanned by a second predetermined amount each iteration until second text data is identified;
• and
• responsive to the second text data being identified, automatically reverting to scanning the first single-page document based on an initial predetermined amount with each iteration;
• and
• responsive to determining the first data corresponds to the one or more document types based on the one or more confidence thresholds, transmit a first notification indicating a first document type match.

A system comprising:

• one or more processors;
• and
• a memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:
• receive a first single-page document;
• scan a first portion of the first single-page document, the first portion based on a first threshold and comprising a first fraction of the first single-page document;
• extract first data from the first portion of the first single-page document;
• determine, using a classifier, whether the first data corresponds to one or more document types of a plurality of document types based on one or more confidence thresholds;
• responsive to determining the first data corresponds to the one or more document types based on the one or more confidence thresholds, cause a graphical user interface (GUI) of a user device to display a first notification indicating a first document type match;
• and
• responsive to determining the first data does not correspond to the one or more document types based on the one or more confidence thresholds:
• iteratively, until a second document type is identified:
• scan a second portion of the first single-page document, wherein the second portion is a second fraction of the first single-page document;
• extract second data from the second portion of the first single-page document, the second portion comprising the first portion and based on a second threshold;
• determine, using the classifier, whether the second data corresponds to the one or more document types of the plurality of document types based on the one or more confidence thresholds, wherein the second portion increases by a dynamically updated predetermined amount each iteration;
• and
• responsive to determining the second data corresponds to the one or more document types based on the one or more confidence thresholds, cause the GUI of the user device to display a second notification indicating a second document type match.