Transportation & Logistics
Trigent has proved its expertise in building complex AI/ML technologies that are stable and well-integrated.
About the Client
Founded in 2007, a privately-owned, third-party logistics provider (3PL) specializes in truckload, intermodal freight, and LTL, as well as offers TMS for freight management. Leveraging logistics expertise with its diverse portfolio of affiliated carriers, the 3PL arranges its customer’s freight with maximum efficiency. With branches spread across four states, the organization ensures fun innovative environment where customers, suppliers, and employees collaborate to provide flexible logistical solutions.
The 3PL acts as the link between shippers and carriers and has an existing system to track, monitor, and assign loads. However, the operations pertaining to quotations and pricing were manual. The manual approach to pricing and quotations involved agents relying on calls and emails with high turn-around time, which affected the organization’s ability to focus on strategic business opportunities.
The organization desired to re-imagine its core business operations to enable agility, speed, accuracy, and efficiency.
They aimed to leverage technology to determine prices that offered the most value to shippers while maximizing sales and margins. By mining their business data, they aimed to anticipate market trends, identify micro-segments for target marketing and track operational business patterns for timely asset management.
The organization felt the need to be self-disruptive and aspired to develop a single source of truth to predict the pricing aptly. However, data silos posed a significant challenge. The organization needed to extract petabytes of data from several sources, such as transaction data, freight data, and data from internal systems, to name a few, related to the following parameters:
The organization sought a team of seasoned experts to help them with adequate domain knowledge and technical know-how to build, deploy and integrate the new solution into its core systems.
The organization decided to invest in developing a Machine Learning (ML) model for price prediction to stay competitive in the market while ensuring minimal disruption to its existing business teams. Being a forward-thinking organization aspired to develop an ML model that had no precedence in the market. Several variables needed to be considered, such as Business Analysis, DevOps, Application development, Core (ML) technology, Cloud infrastructure, and QA, to name a few.
Trigent’s Amoeba Business Framework
The organization partnered with Trigent to leverage its technical knowledge and domain expertise. With the gradual evolution of the project, Trigent’s amoeba business framework enabled the organization to scale up as well as ramp down several critical functionalities in the following stages:
By providing accurate pricing predictions to the customer quote response, the AI/ML-powered model enabled the organization to: