In its earliest iteration, Echo was intended mainly to promote cooperation and sharing of information throughout a company. It was obvious when the project started that different brokers within the company were all receiving different information, much of which they couldn't use themselves, but might be of use to others. The original idea was that users would enter data into software designed to store it, match together trucks and freight, and then notify the relevant users. When the software was first rolled out, it quickly became obvious that manually entering data was simply too time-intensive to be practical. Echo went back to the drawing board.
Going forward, the focus of the project necessarily shifted further towards automation. The goal became to enable all the matching and notification functionality without requiring the users to manually input anything. That goal created technical hurdles that took time to overcome, but making extensive use of machine learning, we've made it. In its current incarnation, Echo is able to identify and extract useful information from emails, match available freight with trucks, then notify relevant users all without human intervention.