Trumansol — Real-Time Logistics Control Center
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Real-Time Logistics Control Center

Trumansol

Building a Real-Time Logistics Control Center That Improved Delivery Predictability by 40%

By Jalal Haider MakkiApril 8, 2026System architecture, dashboard delivery, and workflow implementationUnited States (Georgia)

Maxxsol built Trumansol's real-time logistics control center — a dispatcher dashboard and a synchronized Flutter driver companion app — replacing fragmented manual processes across a large fleet operation. Delivery time predictability improved by over 40% and manual check-ins were eliminated entirely.

40%+
Predictability gain
3
User roles
Real-time
Updates

The problem

Dispatchers, drivers, and operations teams needed stronger visibility across day-to-day logistics workflows and route tracking.

What we built

We built a shared operational system around real-time updates, dashboard visibility, and role-specific workflow support.

  • Real-time logistics dashboard
  • Synchronized driver companion app
  • Geo-location and automated job status updates

The stack & why

Next.jsdispatcher dashboard required real-time data rendering with fast initial load and server-side data fetching
Flutterdriver companion app on Android and iOS; Flutter's rendering performance matches native for GPS tracking and real-time status updates
SupabasePostgreSQL-backed real-time subscriptions fit the logistics data model; row-level security handles multi-role access for dispatchers, drivers, and managers
Nest.jsstructured backend framework suited to complex logistics business logic; dependency injection keeps the codebase testable and maintainable
AWSreliable infrastructure for a mission-critical operations system where downtime directly affects fleet operations
Dockercontainerized deployment for consistent production behaviour and easier scaling

Outcomes

Delivery time predictability improved by over 40%. Dispatchers and drivers now operate from a shared real-time system instead of fragmented manual processes.

Delivery predictability+40%
Manual check-insEliminated
User roles supported3

What we learned

Operations built on Google Sheets and WhatsApp aren't just inefficient — they create invisible single points of failure. When every job assignment lives in a WhatsApp group, one missed message means a missed delivery with no audit trail and no way to know which drivers are idle. The real engineering challenge wasn't building real-time features; it was extracting the implicit dispatch logic that had been living in a dispatcher's head — which driver is closest, which job is urgent, which routes conflict — and encoding it into database schema the system could actually enforce. We ran a careful parallel period where the old WhatsApp workflow stayed live while drivers gradually adopted the new app, which was the only way to cut over a live operation without losing a single delivery.

This project demonstrates

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