This company, headquartered in Ohio was founded in the 1960s and has been active in serving shippers and receivers of international cargo operating in multiple segments, including freight forwarding, ocean freight, trucking, rail operations.
Every day, many cargo ships arrive at a port with numerous products. For audit purpose, customs brokers and trade compliance systems find it difficult to categorize, ie. assign HTS code to all these products for excise duty and other customs duty classification. There are around 21,000+ Harmony Tariff Schedule categories and manually entering it is an incredibly tedious and cumbersome process.
The HTS code is part of a worldwide standardized system of classifying goods in international trade. These are significant unique numbers that are used to identify and determine the different types of products that have been shipped around the world. Large amount of freight data sets makes it tedious and time-taking to group into categories. The input data has a lot of junk and incomplete data. It is also very difficult to update any new variations to the listed products.
Thanks to TechMobius’s unique AI and Machine Learning technology, no matter what the size of the data set, accurate mapping of it can be done in record time. The process begins with the file with freight description being uploaded. The code classifier web portal identifies the HTS code and displays confidence score. This is then sent to the custom broker. IF, the confidence score is less than 0.7, then the code is looped into the AI interface which intervenes to re-verify. Only once it passes the confidence score above 0.7, is it sent to the custom broker.
The HTS code’s purposes include trade statistics, internal taxes, trade policies, rules of origin, freight tariffs, transport statistics, price monitoring, and economic research & analysis.
But due to the sheer volume of data, accurate classification of goods is a very time-consuming and cumbersome process. Thanks to TechMobius’s state-of-the-art technology, no matter what the size of the data set, accurate mapping of it can be done in record time. The cost and resources are effective too. Our smart technology easily combs through large volumes of junk, incomplete and unnecessary data. All of this, in a fraction of time that would be spent if done manually.