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Modernizing Logistics Allocation System for Global Shipping Efficiency

n-ix.com

Logistics

Transportation

Technology

Inefficient Cargo Allocation in Legacy Logistics System

The client's legacy system lacked real-time vessel/container tracking, prioritization capabilities, and multimodal transportation integration, resulting in suboptimal resource utilization, increased operational costs, and limited visibility across the logistics chain.

About the Client

A multinational logistics company specializing in global cargo transportation, operating marine ports and intermodal logistics networks across 100+ countries

Enhance Logistics Efficiency through System Modernization

Implement intelligent cargo prioritization algorithms
Establish real-time visibility across transportation modes
Expand US market capabilities through railway integration
Improve system reliability through automated testing
Optimize resource allocation using predictive analytics

Core Logistics Modernization Requirements

AI-driven cargo prioritization engine with dynamic re-allocation
US railway station integration for intermodal transportation
Real-time vessel/container status dashboards with segmentation
Automated email notifications for capacity alerts and errors
Kafka-based event streaming for system integration

Technology Stack Requirements

Angular

Kotlin

MS SQL Server

Apache Kafka

Mockito

JUnit

System Integration Needs

Legacy desktop platform data bridge
US railway station tracking API
Vessel telemetry systems
Customer CRM for demand forecasting

Operational Requirements

99.9% system availability with horizontal scalability
Real-time data processing under 500ms latency
Role-based access control with GDPR compliance
Automated recovery for failed allocation processes

Optimized Logistics Operations and Cost Efficiency

Implementation will reduce container misallocation costs by 30%, improve vessel capacity utilization by 25%, enable 40% faster US market expansion, and decrease operational downtime through enhanced system visibility and automated processes.