Vantage Analytics
A real-time supply chain analytics platform that transforms raw logistics data into actionable insights, reducing delivery delays by 34% through predictive route optimisation.
Project Overview
Vantage Analytics was built for a regional logistics company managing a fleet of 200+ vehicles across three distribution centres. Their operations team was making routing and scheduling decisions based on spreadsheets and gut instinct, with no visibility into real-time performance metrics or predictive delay signals.
We delivered a full-stack analytics platform that ingests telemetry from GPS trackers, warehouse scanners, and ERP systems, then presents real-time dashboards, historical trend analysis, and ML-powered delay predictions — giving operations managers the data they need to make faster, better decisions.
Technical Architecture
The data ingestion layer is written in Go for maximum throughput — it processes over 50,000 telemetry events per minute from GPS devices, barcode scanners, and warehouse IoT sensors. Go's concurrency model lets us handle bursty traffic from fleet check-ins without dropping events or adding latency.
Predictive models are built in Python using scikit-learn for delay probability scoring and route optimisation. The models are trained on two years of historical delivery data and incorporate real-time signals like weather, traffic, and warehouse queue depth. Predictions are refreshed every 15 minutes and surfaced directly in the dashboard.
The frontend is a Next.js application built with React, TypeScript, and Tailwind CSS, deployed on Vercel for instant global access. The dashboard features interactive maps, drill-down charts, and configurable alert thresholds — all rendering in real time via WebSocket connections to the backend.
PostgreSQL stores structured logistics data with time-series partitioning for efficient historical queries, while Redis powers the real-time layer — caching live vehicle positions, active route calculations, and session state for dashboard users.
Infrastructure is provisioned with Terraform on AWS, with the ingestion and API services running in Docker containers on Kubernetes. Auto-scaling policies ensure the platform handles Monday-morning fleet dispatches (10x normal traffic) without degradation.