Document AI Fields

Umango can use artificial intelligence (AI) to analyze documents and automatically capture data based on a pre-trained or custom document type.

You can choose to enable AI fields at any time in the life cycle of a job. AI can be enabled and disabled using the Enable AI Document and Disable AI Fields buttons located within the zones tab.

Enabling Document AI

Disabling Document AI

Enabling an AI Document Type in a Job

You may find that AI is not required or that other methods of data capture are more suited to your requirements. You may also find that your documents are not suited to capturing with AI.

Note: It is strongly recommended that AI fields be disabled unless you require them in your job. AI processing adds a significant time overhead to your document processing.

To learn more about AI Document Types, their capabilities, and how to train Custom AI Documents, read the AI Document Types section.

Selecting A Document Type

For the purpose of AI capture, document types fall into 3 basic categories:

    1. Semi-structured documents: The data expected on the documents is reasonably consistent but its location may not be. These documents are typically suited to Pre-trained or Custom Neural document types. Examples include invoices, business cards, receipts etc.
    2. Structured Documents: The appearance of the document and the data it contains is consistent. Data will be located in the same location on every document processed. These documents are typically suited to Pre-trained or Custom Template document types.
    3. Unstructured Documents: The data on the documents will be located anywhere within the document and the type of document does not fall into one of the available semi-structured document types. These documents may be suited to Custom Neural document types.

AI Data Field Categories

During processing the AI engine will search for data common to the AI Document Type selected. These data fields are known as "standard fields" in Umango and in most instances are preferred. In addition, the AI engine may find data that it thinks is useful and these additional data values are called "structured document fields". These structured document fields may not appear on every document and should only be used in cases where the documents to be processed will be very similar to the job's sample documents.

For example, when processing invoices, Umango will try to find an invoice number, invoice date, part numbers, item quantities and an invoice total etc. These are among the data fields expected on every invoice and will consistently be captured if present anywhere on the document. These are "standard data fields". In addition, peripheral data fields may be found. These "structured fields" are useful when all the documents to be processed in a job will be the same structure. For example, if all the invoices to be processed in a job will to be coming from the same supplier then the structured fields would be consistently captured and usable.

All data captured using the structured document type option will be captured as "structured document fields".

For details on configuring Umango to validate AI field data within a zone, read the zone properties section.