Appzen, Inc.

Amrit Singhal

Edris Naderan

Ankit Bansal

Akash Vijay Hajare

A non-transitory computer readable storage medium has instructions executed by a processor to access a purchase order data set. An invoice data set is ingested. Tuples of purchase order line-items from the purchase order data set are gathered. Tuples of invoice line-items from the invoice data set are formed. Positive training samples are created, where each positive training sample comprises a selected purchase order line-item and a corresponding invoice line-item. Negative training samples are formed, where each negative training sample comprises a fabricated purchase order line-item and a corresponding invoice line-item. A machine learning model is trained with the positive training samples and the negative training samples to form a trained purchase order machine learning model. An accounts payable invoice is received. The trained purchase order machine learning model is used to match an accounts payable invoice line-item to a purchase order line-item.

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Sunnyvale, CA, United States of America

Amrit Singhal