Case Study : TransVoyant: Asset Tracking Solution for Supply Chain and Logistics AI Platform

Brief

Apache Kafka project integrating real-time shipping and logistics data.

Problem

TransVoyant was struggling with processing container shipment data from trucking and shipping companies from around the world, with wildly varying standards. Tracking product movements from vendors to distribution centers was a critical pain point. Additionally, TransVoyant was experiencing
problems with the regularity and accuracy of source data from these various global vendors.

Solution

Becoming Machinic created a solution that optimizes TransVoyant’s logistic pipeline, so that distributors are able to minimize their stock in warehouses and distribution centers, creating a unique benefit for TransVoyant’s customers. Becoming Machinic built a business process automation that ingests all trucking and container shipment data and determines how likely the data is accurate, with regard to tracking, delivery time, and what the shipments actually contain. The process then gives a “trustworthiness” rating to its source. This process produces a uniform system output based on that data. The end result is a solution that intelligently transforms the noisy and variable quality of container shipment data to produce smooth, reliable output for TransVoyant.

Additionally, Becoming Machinic created an app for the client that predicts arrival time, and supports roughly 300 connected applications.

Highlights

PostgreSQL, Apache Kafka, Spring Boot, Apache Spark, data security, government contracts.

Industry

Logistics, Shipping
SIC: 73,737
NAICS: 541,541511

Location

Alexandria, VA

Product

machinic.io

Business Processes Optimized

Tracking Shipping Container Data;
Standardizing Container Data