AI-powered logistics management

24%
reduction in logistics costs
30+
logistics constraints modeled
AI-powered logistics management
Read how we've contributed to the development of proprietary algorithms for solving logistics and transportation issues.
Location:

Germany

Team Size:

6 engineers

Technologies
PHP
Laravel
Cassandra
Nginx
GitHub
Docker
Ansible
Microsoft Azure
Groovy
Heap
Amazon SNS
EC2
Route53
CloudFront
01

About the Client

The main goal of the customer — a global provider of supply chain optimization solutions for various industries — was to support and enhance their existing platform for all logistics and transportation activities.

AI-powered logistics management
02

Project Overview

Over a two-year period, our development team collaborated closely with the client to build a robust and scalable logistics management system. The solution includes three integrated components:

Web App for Managers

Enables complete supply chain visibility, carrier selection, delivery/load plan optimization, and performance tracking via BI dashboards.

Mobile App for Deliverers

Provides real-time task creation and delivery tracking, improving service quality, and ensuring transparency across all delivery stages.

Mobile App for Clients

Allows customers to place orders and monitor their delivery status, improving user satisfaction and reducing communication gaps.

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03

Solution we Delivered

The platform streamlines logistics operations through intelligent tools designed to optimize routes, manage inventory, and enhance overall operational efficiency. Core system capabilities include:

  • Real-time GPS tracking of vehicles
  • Automatic generation of optimal routes (load capacities, multiple time windows, cross-docking, and other indicators)
  • Inventory management
04

Our Contribution

Our team played a key role in designing proprietary algorithms that tackle complex logistics challenges:

AI-Powered Vehicle Routing

Developed a dynamic AI-driven algorithm that accounts for over 30 parameters (including vehicle weight/volume capacities and delivery time windows) to generate the most efficient routing plans in real-time.

3D Loading & Inventory Allocation

Created a logic engine that optimally assigns orders to vehicles while considering their physical dimensions. The 3D loading algorithm visually simulates cargo placement based on length, width, and height, helping avoid wasted space and increasing load efficiency.

Inventory Routing Optimization

The system uses predictive logic to balance order scheduling and stock levels, helping minimize stockouts and reduce distribution costs. AI-based planning enhances both forecast accuracy and responsiveness.

05

Client’s Results

Continuous optimization and iterative development led to significant operational improvements for the client. As a result, the platform enabled:

  • More efficient transportation plans across their delivery network
  • Reduced overall logistics and distribution costs
  • Increased vehicle utilization and productivity
  • Improved profitability on every shipment

Up to 50% fewer critical system errors.

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