Enterprise Logistics Platform

Enterprise logistics platform for vehicle operations, workflow orchestration, and internal fleet visibility.

2026

  • Java
  • Spring Boot
  • API Gateway
  • Microservices
  • PostgreSQL
  • Flyway
  • Expo
  • React Native
  • OCR-Assisted Tracking
  • Docker Compose

This platform was designed for Autotrend to replace fragmented vehicle-movement processes with a structured logistics system across mobile and web. It coordinated requests, confirmations, planning, notifications, key-status tracking, and vehicle localization across internal departments under one operational model.

Enterprise logistics platform architecture diagram showing request intake, workflow orchestration, tracking evidence, and enterprise support services.
Architecture graph: vehicle requests flow through identity, logistics orchestration, tracking evidence, notifications, and analytics services for controlled execution.

Problem

Autotrend needed a structured way to coordinate internal vehicle movement across logistics, commercial, workshop, administration, and IT without relying on fragmented manual processes.

Constraints

  • Workflows had to support different roles, permissions, and ownership boundaries across departments.
  • Request execution needed explicit state transitions with accountability for planning, rescheduling, departure, arrival, completion, and cancellation.
  • Vehicle records had to be enriched from operational activity through photo, GPS, and OCR-based evidence handling.

Architecture

  • Enterprise microservices split across API gateway, identity, logistics, tracking, notifications, analytics, and prioritization domains.
  • Role-based access control with internal data ownership boundaries and Flyway-managed schema evolution.
  • Mobile and web delivery for request creation, logistics coordination, confirmations, and execution tracking.
  • Outbox, inbox, and DLQ reliability patterns to protect cross-service workflow delivery and recovery.

Tradeoffs and Failures

  • Strong workflow control improved auditability but required careful handling of exceptions and reschedules.
  • Service separation improved maintainability and rollout readiness while increasing integration and contract-governance pressure.
  • Evidence-rich localization improved fleet visibility but introduced additional review steps for image quality, OCR confidence, and GPS consistency.

Engineering Impact

  • Replaced ad hoc coordination with a controlled end-to-end request and confirmation lifecycle.
  • Improved operational visibility through notifications, key-status tracking, and localization evidence flows.
  • Established a backend foundation prepared for future infrastructure hardening and broader enterprise rollout.

Outcomes

  • Clearer accountability across status changes and handoffs between departments.
  • Better internal visibility into vehicle location, planning state, and execution progress.
  • More scalable logistics operations through explicit service boundaries and governed API contracts.

What Made This Approach Different

The platform treated internal logistics as an operational system of record, not just a request board. Vehicle movement, confirmations, notifications, key tracking, and localization evidence all belonged to one controlled workflow model.