Leading Trucking company

The fourth-largest asset-based truckload carrier by revenue in the United States surpassed the $1 billion mark in annual revenue faster than any truckload carrier in history. Read more to find out how they went from 48 trucks to 7,000 tractors and 15,500 trailers with on-the-go tech integrations.

The Problem Statement

The client was facing high levels of driver churn due to drivers facing issues like absence of stabilized income, missing home times, disrupted personal lives and severe amounts of manual paperwork processing.

Services
Delivered

DCT provided enterprise-grade tools and solutions that enabled world class communications, navigation, geolocation, and connectivity. An intuitive platform was built for drivers, where operational processes were automated with zero or one-touch driver activity. Our driver App helped bridge the gap between the physical and digital world, modernizing their core systems to accelerate innovation and delivered experiences that delighted their biggest assets - their drivers.

KEY DIFFERENTIATORS

  • Our app enabled drivers to plan their journey effectively.
  • Drivers could schedule and plan their home time easily, thus maintaining their work-life balance.
  • Drivers could check their next revenue assignment with turn-by-turn navigation.
  • DCT initiated graph databases and visualization which solved one of the most pressing data challenges centered around connections, not just discrete data.
  • Our interconnected view of data helped build intuitive relationships to identify and access management quickly and effectively.
  • Social network graphs that leverage social connections or infer relationships based on activity were introduced.
  • We built a native graph processing engine that supported high-performance graph queries on large master datasets to enable real-time decision making.

Graph Database and visualization

One of the most pressing data challenges centered around connections, not just discrete data. They needed a connected data technology – a graph database to overcome these challenges.

  • Our interconnected view of the data helped build intuitive relationships to identify and access management quickly and effectively.
  • Social Network graphs that can leverage social connections or infer relationships based on activity when using a graph database to power the drivers social network application.

We are building a native graph processing engine that supports high-performance graph queries on large master datasets to enable real-time decision making.

Mitigation

We built a native graph processing engine that supported high-performance graph queries on large master datasets to enable real-time decision making.