Case Study: CargoCast achieves scalable AI-powered cargo flow predictions with SEEBURGER BIS Platform

Cargo flow predictions based on integrated logistics data and artificial intelligence (AI)

Cargocast, an innovative logistics startup, sought to provide AI-powered cargo flow predictions but faced challenges in integrating data from its diverse and heterogeneous client base, which included freight forwarders and logistics companies with varying IT systems and capacities. Manually acquiring and transforming this data into a usable format for its AI engine was a complex undertaking that hindered scalability. To overcome this, Cargocast implemented the SEEBURGER BIS Platform to streamline the connection and data integration process.

The SEEBURGER BIS Platform provided a fast, secure, and reliable solution for connecting all partner systems via APIs and FTP/SFTP, automatically consolidating and transforming large volumes of raw logistics data into the required target structures. This resulted in a simplified integration process that increased Cargocast's scalability and provided reliable, monitored processes for rapid error correction. By ensuring a complete and high-quality database for its AI algorithms, SEEBURGER enabled Cargocast to offer its customers accurate, daily forecasts for optimal resource planning.

CargoCast

Christoph Schäfer

Lead Developer