AI route optimization that cut fuel costs 28%
An end-to-end AI/ML logistics platform for a 120-vehicle fleet: routes computed in 200 ms, deliveries 35% faster, and every dispatcher spreadsheet retired.
01 · The Challenge
Routes built by hand, money left on the road
SwiftLogistics ran 120 vehicles across 3 depots, handling 2,000+ deliveries a day. Every morning, dispatchers spent three hours building routes in spreadsheets, routes that ignored live traffic, wasted vehicle capacity, and arrived late while diesel prices kept climbing.
Of manual route planning, every single morning
Dispatchers stitched routes together in spreadsheets before the first truck could leave, and one sick day meant chaos.
Of vehicle capacity driven around empty
Parcels were assigned by habit, not by weight, volume, or geography, so half-empty vans burned full-price diesel.
Customer satisfaction, below industry benchmark
No live ETAs, no proactive alerts, customers called the depot to ask where their delivery was, and late drops damaged NPS.
Year-over-year fuel bill growth, no strategy
Competitors with digital logistics platforms were undercutting on price while SwiftLogistics absorbed every wasted kilometre.
THE BRIEF
Replace spreadsheet routing with AI. Give dispatch a live map of the whole fleet. Give drivers turn-by-turn routes that react to traffic. Give customers accurate ETAs, automatically.
02 · The Solution
A three-layer AI logistics platform
Route intelligence for the algorithm, a live console for dispatch, and a mobile app for every driver, deployed across 3 depots in 5 months as part of our AI development services.
AI Route Engine
A Python optimization service built on Google OR-Tools and live traffic data, computing the cheapest, fastest multi-stop routes for 200 deliveries in under 200 milliseconds.
Operations Dashboard
A real-time React console giving dispatch a live map of every vehicle, ETAs for every stop, fuel metrics per route, and one-click reassignment when plans change.
Driver Mobile App
A React Native app with turn-by-turn navigation, proof-of-delivery capture, and automated customer ETA notifications, fully offline-capable when signal drops.
Operations Console
Dispatch sees the whole fleet on one screen
The three-hour spreadsheet ritual became a five-minute review. The engine proposes routes; dispatch approves, adjusts, and watches them run, with live GPS pings every 10 seconds.
03 · The Intelligence
Three ML models doing the heavy lifting
Trained on two years of the client's own order and telematics history, not generic data.
Demand forecasting
An LSTM network predicts next-day delivery volumes per zone, so depots pre-position vehicles before the orders even arrive.
Dynamic re-routing
Traffic, road closures, or urgent same-day orders trigger a recalculation pushed to affected drivers within 30 seconds, no dispatcher needed.
Predictive maintenance
Telematics analysis (RPM, braking, engine temps) flags vehicles likely to need service in the next 14 days, breakdowns previously cost 6% of fleet uptime.
04 · The Build
Five months from route audit to full fleet
Four phases, each de-risking the next: the AI ran in parallel with the old spreadsheet process until it consistently beat it, then took over depot by depot.
We start with a two-week route audit on your real delivery data, so you see the savings before committing.
Book a Route Audit →Route audit & data pipeline design
Current-state route audit across all 3 depots, driver interviews, an integration blueprint for the existing SAP TMS, and the data pipeline that would feed ML training.
Route engine, dashboard & driver app
The VRP optimization engine, GPS telematics via AWS IoT, the React operations dashboard, the React Native driver app, and the REST API layer on MongoDB.
Training, back-testing, parallel runs
LSTM demand forecasting trained on 2 years of orders, re-routing back-tested against historical traffic, maintenance model calibrated, all validated in a parallel run against the manual process.
Pilot, then all 3 depots
A 20-vehicle pilot at depot 1, then full fleet onboarding. All 120 drivers were trained in a single day using an in-app guided tour and a train-the-trainer model.
Tech Stack
What the platform is built on
Every layer chosen for sub-second route solves and fleet-scale telemetry.
Your Fleet Next
Ready to optimize your logistics?
Whether you run 20 vehicles or 2,000, a route audit on your real delivery data shows the savings before you commit to a build.
05 · The Results
Ninety days after go-live
Measured across all 3 depots, comparing the quarter before launch with the quarter after.
Dispatch used to start at 5 AM with spreadsheets. Now the routes are ready before anyone walks in, and our fuel bill dropped by more than a quarter. It paid for itself in the first two quarters.
FAQ
Questions logistics teams ask us
How fast does the route engine compute optimized routes?+
The OR-Tools VRP solver returns optimized multi-stop routes for up to 200 deliveries in under 200 milliseconds. Larger batches parallelize across AWS Lambda and still return within 2 seconds.
Can it integrate with our existing TMS or ERP?+
Yes. A REST API layer was built specifically for third-party integration. SwiftLogistics connected their existing SAP TMS in 2 weeks with zero downtime using a webhook-based connector. CSV import, REST, and SFTP integrations are all supported.
How is GPS and customer data secured?+
All location data travels over TLS 1.3 and is stored encrypted at rest in AWS with per-depot access controls. Customer PII is pseudonymized in analytics exports, and the platform is GDPR-compliant by design.
What happens when a driver loses signal?+
The driver app caches the current route and works fully offline. When connectivity returns, it syncs proof-of-delivery photos, stop completions, and re-routing updates automatically, no data is lost.
How long does driver onboarding take?+
Drivers are fully productive within one working shift. SwiftLogistics trained all 120 drivers in a single day using a train-the-trainer model plus the in-app guided tour.
Can the system handle multi-depot operations?+
Yes, it was built for a 3-depot operation from day one. Each depot plans routes independently with shared fleet analytics, cross-depot reassignment, and one unified management dashboard.
Talk to us about your fleet
Share your fleet size and delivery volume, and we'll come back within 24 hours with an approach and a fixed-price estimate.