As Artificial Intelligence (AI) systems grow in complexity and scope, managing end-to-end workflows, spanning data ingestion to model deployment, has become increasingly labor.
How a Renowned Freight Forwarding Company Enhanced Their Operational Efficiency by 40%
Meet The Client
The client, a renowned logistics and freight forwarding company in the US, specializes in providing customized freight forwarding services, including air, ocean, and ground transportation, as well as warehousing and distribution solutions. With over 400 employees nationwide, the company surpassed the billion-dollar revenue mark in 2017. Their expertise extends to handling complex logistics challenges efficiently and reliably.
Challenges
The client encountered several challenges:
Fragmented data sources scattered across various systems
Inconsistencies in financial data
Lack of integration among existing systems
Siloed data and disjointed workflows
Limited visibility into key financial metrics and performance indicators
Solutions
The freight forwarding company considered multiple technical implementations to address the challenges of implementing centralized financial system:
5 Min Read
Fragmented data sources scattered across various systems
