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( WiseTech Global / 2024 – 2026 )

Trinium TMS

Transitioned a legacy desktop TMS toward a modern, scalable web platform through a structured module-by-module conversion on MUI, improving usability and operational efficiency across daily workflows

My role
Lead Product UI/UX Designer, CargoWise Landside
Timeline
2024 – 2026
Category
Enterprise SaaS / Intermodal TMS / Legacy Modernization
Status
Redesign, delivered

Tools Figma, MUI (Material UI) Design System

Generated schematic standing in for imagery of Trinium TMS. It depicts nothing.
Generated schematic, not a screenshot of Trinium TMS.

Generated schematic, not a screenshot. Real imagery to follow.

( The account )

Context

CW Trinium is an intermodal Transportation Management System (TMS) inside the CargoWise ecosystem, used by drayage and trucking companies to run the daily movement of shipping containers between ports, rail terminals, container yards, and warehouses. It sits at the operational heart of intermodal freight: dispatchers, operations managers, and drivers rely on it as their central command system for container dispatching, driver assignments, order logistics, and real-time fleet operations. The domain it serves is high-volume, time-sensitive, and regulation-heavy, where operational efficiency directly affects profitability.

Trinium was originally a legacy desktop application, built on older technology and workflows that were not designed for modern web-based usage. This project focused on transitioning it into a scalable, web-based TMS: redesigning legacy modules into web-friendly workflows, improving usability, and adding capabilities the legacy system never had. The work was structured as a module-by-module conversion driven by business requirements, rather than a single big-bang rewrite.

The problem

The legacy Trinium system carried compounding operational and usability challenges that made an already demanding job harder for the people running freight operations:

  • Outdated, unintuitive interface: the legacy UI lacked modern navigation patterns, clear information architecture, and efficient workflows. Dispatchers worked around cluttered screens and rigid layouts that did not adapt to their real operational needs.
  • Poor scalability: the desktop architecture could not scale to the growing volume and complexity of logistics operations. Many processes took multiple steps, lacked visibility, or were simply hard to use efficiently.
  • No bulk operations: handling large volumes of orders, updates, and assignments meant tedious one-by-one interactions with no batch processing.
  • Fragmented communication: driver-to-dispatcher coordination depended on external phone calls, texts, and third-party apps, creating information silos and delays during time-critical operations.
  • No intelligent automation: despite sitting on rich operational data such as driver locations, container statuses, delivery schedules, and Hours of Service compliance, the system offered no AI-driven help with planning or decisions.
  • Disconnected workflows: order creation, driver assignment, route planning, billing, and document management existed as siloed processes, forcing constant context-switching between screens and modules.

What I did

The approach was to transition Trinium from a legacy desktop TMS into a modern, scalable web platform built on MUI (Material UI) as the foundational design system, converting the product module by module against business requirements. Rather than replicate legacy patterns on the web, each module was reworked for improved usability and structure, and several were extended with capabilities the legacy system did not have.

I first established the overall UI direction for the web platform. Once that was discussed and approved, I moved through the modules in turn. Order Management was completely redesigned around a table-based order list with efficient row actions (Edit, Delete, Duplicate, Mass Update, Add Order), a modal-based Quick Add using progressive accordion sections for fast entry, and a full-page order creation screen with side-panel tab navigation across Order, Schedule, Container, and Chassis, supporting Pickup, Hook, and Delivery legs for complex orders. On top of the redesigns, new capabilities addressed the legacy gaps directly: a Mass Update feature for editing many orders at once, an AI-powered natural language dispatch planning interface, a consolidated Communication Centre, and map-based visual dispatching. A wide set of additional modules were redesigned to complete the platform, from Street Turn Criteria, Rail Billing, AR/AP, and Driver Itinerary and HOS to a Customer Portal, document upload and transfer, a customizable dashboard with configurable widgets, and a modernized sidebar, navigation, and menu system with AI chat integration.

Outcomes

  • Transitioned a legacy desktop TMS toward a modern, scalable web platform through a structured module-by-module conversion on MUI, improving usability and operational efficiency across daily workflows
  • Redesigned Order Management into a structured system (table-based list, modal Quick Add, and full-page multi-leg creation) that made high-volume order handling faster and clearer
  • Introduced bulk order editing through a new Mass Update feature, replacing tedious one-by-one interactions when managing large datasets
  • Designed an AI-powered natural language dispatch planning capability with no legacy equivalent, turning plain-language intent into optimized, reviewable plans
  • Consolidated fragmented phone, text, and third-party coordination into a single Communication Centre with messaging, notifications, and AI-assisted email
  • Used MUI as the shared design system between design and engineering, which streamlined handoff and reduced implementation friction since developers built against the same component library

What I learned

Modernizing a legacy operational system is really about workflows, not screens. The most valuable work was not making Trinium look current, it was reworking how dispatchers actually move through orders, assignments, and communication. Converting module by module against business requirements, and analyzing the legacy pain points inside each one before redesigning, kept the effort anchored to operational reality instead of surface polish, which matters most in a high-volume, time-sensitive domain where every extra step has a cost.

Introducing AI into an operational tool works best when it speaks the operator's language and keeps them in control. Framing dispatch planning as a natural language interface met dispatchers where they already are, but the design still had to expose the plan clearly and let them review, approve, reassign, and resolve conflicts at the leg level. The lesson was that automation earns trust in this kind of system by being legible and reversible, not by being fully hands-off.

A shared design system is a delivery decision as much as a design one. Building on MUI, the same library engineering used, meant the redesign was not just easier to hand off but easier to implement faithfully. In a large, module-by-module modernization, that shared foundation is what keeps a long conversion coherent across many surfaces and many handoffs.

( Tags )

  • Enterprise SaaS
  • Logistics
  • LogTech
  • Supply Chain
  • Intermodal
  • Drayage
  • TMS
  • Fleet Operations
  • Dispatch
  • Legacy Modernization
  • Web Modernization
  • AI Product Design
  • Natural Language Interface
  • Bulk Operations
  • Communication Design
  • Data Tables
  • Information Architecture
  • Design Systems
  • Material UI
  • Responsive Web