Over the last five years, we have been obsessed with introducing new technology to dramatically improve the efficiency of the freight brokerage business. This effort not only includes creating a better experiences for shippers and carriers, but also improving and automating back-office processes.
Every broker receives thousands of documents per month related to ongoing and delivered shipments: Rate Confirmations, BOLs, PODs, Invoices, etc. Identifying, separating, cataloging and uploading each document to the right place takes countless hours, and even the most strict processes result in a non-negligible error rate.
The new feature we just released is a machine learning model that analyzes each email, its attachments, and identifies what documents are contained into a single or multiple PDF files. After automatically scanning and cataloging the content of the files, the system then splits the documents into its component sub-files (e.g. BOLs, Invoices, Rate Confirmations, etc.) and auto-uploads each document to the right shipment folder. This new feature is saving hundreds of hours per month in document review, and it has dramatically reduced the error rate in classifying documents.
The more automated and efficient we are, the lower operational costs we have, which in turn has meant we offer more attractive prices for shippers and better margins for carriers.