Custom freight management system for agricultural logistics
Challenge
The client, a large agricultural exporter, relied on multiple Excel files to manage freight quotations, shipment planning, and carrier coordination. Seasonal volumes, multiple transport modes, cross-border operations, and changing freight rates made these workflows increasingly difficult to manage. Sales and logistics teams lacked a single source of truth, quotation processing was slow and error-prone, and fragmented data limited visibility across shipments. The company needed custom freight management software capable of supporting complex agricultural logistics operations and replacing spreadsheet-based processes with a centralized system.
The client, a large agricultural exporter, relied on multiple Excel files to manage freight quotations, shipment planning, and carrier coordination. Seasonal volumes, multiple transport modes, cross-border operations, and changing freight rates made these workflows increasingly difficult to manage. Sales and logistics teams lacked a single source of truth, quotation processing was slow and error-prone, and fragmented data limited visibility across shipments. The company needed custom freight management software capable of supporting complex agricultural logistics operations and replacing spreadsheet-based processes with a centralized system.
Solution
Adexin developed a custom Excel-to-Web freight management system that centralized shipment, quotation, customer, and carrier data. The platform included a quotation engine for comparing freight rates by cargo type, transport mode, and destination, as well as client and carrier databases, active delivery management, advanced filtering, role-based access, and configurable fields. The system was designed around seasonal agricultural logistics workflows and supported road, sea, and air transportation. The technology stack included TypeScript, Node.js, NestJS, React, PostgreSQL, and AWS.
Adexin developed a custom Excel-to-Web freight management system that centralized shipment, quotation, customer, and carrier data. The platform included a quotation engine for comparing freight rates by cargo type, transport mode, and destination, as well as client and carrier databases, active delivery management, advanced filtering, role-based access, and configurable fields. The system was designed around seasonal agricultural logistics workflows and supported road, sea, and air transportation. The technology stack included TypeScript, Node.js, NestJS, React, PostgreSQL, and AWS.
Results
The new freight management system reduced quotation processing time by more than 90%, allowing teams to move from hours of manual work to minutes. Manual data-entry errors decreased by 80%, while more than 50 operational data points were consolidated into a single interface. The platform achieved 100% adoption across regional logistics teams within six weeks. By replacing fragmented spreadsheets with a centralized operational system, the client gained faster access to freight rates, better shipment visibility, and a more scalable process for managing seasonal logistics demand.
The new freight management system reduced quotation processing time by more than 90%, allowing teams to move from hours of manual work to minutes. Manual data-entry errors decreased by 80%, while more than 50 operational data points were consolidated into a single interface. The platform achieved 100% adoption across regional logistics teams within six weeks. By replacing fragmented spreadsheets with a centralized operational system, the client gained faster access to freight rates, better shipment visibility, and a more scalable process for managing seasonal logistics demand.