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Real client project — EV fleet operations in Singapore

EV Fleet AI Dashboard

Illustrative example, not verified client data

A Singapore-based electric vehicle distributor operating one of the largest EV charging hubs in the region needed a way to centralise fleet operations, driver scheduling, and charging logistics. IonicX built an AI-powered dashboard to bring everything into one system.

Problem

  • Fleet operations data was spread across multiple systems with no unified view of vehicle status, locations, or availability.
  • Driver scheduling and shift assignments relied on manual coordination, creating gaps and inefficiencies.
  • Charging logistics across dozens of DC charging points needed better rotation planning to avoid bottlenecks and downtime.
  • Dispatch communications with drivers were fragmented, with no standardised way to push schedule changes or route updates.

System

  • Built a centralised fleet intelligence dashboard showing real-time vehicle status, driver assignments, and charging schedules.
  • Integrated AI-powered scheduling intelligence to optimise driver shift assignments and charging rotations based on fleet utilisation patterns.
  • Connected WhatsApp for dispatch communications, allowing management to push schedule updates and route changes directly to drivers.
  • Created management reporting views for fleet utilisation, charging throughput, and workforce allocation.

Current outcome framing

  • Centralised fleet visibility replaced scattered tracking across multiple systems.
  • Automated driver scheduling reduced manual coordination overhead for fleet managers.
  • WhatsApp-based dispatch gave drivers instant access to schedule changes and route updates.
  • Real-time charging status tracking improved rotation planning across all DC charging points.

Problem to system workflow

  1. Step 1Fleet data from vehicles and charging points feeds into the dashboard in real time.
  2. Step 2AI scheduling engine analyses utilisation patterns and suggests optimised driver rotations and charging schedules.
  3. Step 3Dispatch notifications are sent to drivers via WhatsApp for shift changes, route updates, and charging assignments.
  4. Step 4Management monitors fleet status, driver performance, and charging throughput from a single dashboard view.

What IonicX AI would build

Next.js dashboardSupabaseWhatsApp Cloud APIAI scheduling engine

Important note

This page is intentionally framed as a realistic illustrative example only. It exists to show how an IonicX AI rollout could be structured when verified client metrics are not being published.

Related pages

ai fleet management singaporeev truck dashboardai logistics automationView full portfolio

FAQ

What makes this different from a standard fleet management tool?

This dashboard was built specifically for EV fleet operations, combining workforce scheduling with charging logistics. Unlike generic fleet tools, it accounts for charging rotations and EV-specific constraints alongside driver management.

Can AI really optimise fleet scheduling?

AI handles the pattern-matching well — analysing which vehicles need charging, which drivers are available, and where bottlenecks form. The scheduling suggestions still go through a manager for approval, but the analysis saves significant planning time.

Why use WhatsApp for driver dispatch instead of a dedicated app?

Drivers already use WhatsApp daily. Building dispatch on WhatsApp means zero adoption friction — no new app to install, no training needed. Messages arrive on the same platform drivers already check constantly.

Want IonicX AI to build the real version of this for your business?

Share your current enquiry flow, bottlenecks, and growth target. We will map the right website, chatbot, WhatsApp, booking, pricing, and AEO/GEO rollout for your Singapore business.

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