AI logistics Singapore

Keep your fleet moving, not waiting.

Every extra litre of fuel and every unplanned maintenance stop cuts into your margin. Tan & Co. reads traffic, weather, GPS, and vessel data to plan each leg with greater control.

Optimise Your Logistics with AI See the tools

Live route modelSingapore hub

Port
operations

12% more efficient on route-optimised plans

Built for daily operations

AI tools that make logistics decisions clearer.

Dispatchers get a plan that reflects the road as it is now. Maintenance teams get warning before a small fault becomes a costly stop.

Dynamic route optimisation

Recalculate multi-stop routes every 15 minutes using live GPS, traffic conditions, delivery priority, and vehicle limits.

Up to 22% lower fuel cost

Delivery scheduling automation

Assign slots around vehicle capacity, driver hours, loading time, and customer windows. Exceptions reach a person quickly.

31% fewer late deliveries

Predictive maintenance

Combine engine temperature, vibration, fuel use, and maintenance history to flag likely failures up to 14 days ahead.

18% lower dry-dock cost

Resource deployment

Match trucks and drivers to demand while balancing workload, route length, skills, and return-to-depot requirements.

Higher asset utilisation

Operations control room

Give managers one view of stops, delays, capacity, and service-level risk across the fleet and its active jobs.

Faster exception handling

Performance reporting

Track cost per stop, on-time delivery, idle time, and asset use so each planning change has a measurable result.

Decisions backed by data

31%fewer late deliveries

92%on-time delivery, up from 78%

19%lower fuel cost

Singapore freight forwarder

2,500 daily stops. Fewer surprises.

A 200-plus vehicle freight forwarder connected its TMS to Tan & Co.'s dynamic scheduling and route optimisation API. The planning engine adjusted for traffic, customer windows, vehicle capacity, and driver hours before dispatch.

Dispatchers now spend their time on exceptions instead of rebuilding routine plans.

"Our dispatchers now manage exceptions, not routine plans."

Predictive maintenance vessels

Know when a vessel needs attention.

Small signals matter. The model learns from your maintenance logs and sensor readings, then sends a practical alert before failure disrupts a sailing plan.

Fourteen days of warning can change the schedule.

A regional shipping line cut dry-dock costs by 18% and unplanned downtime by 40% after its engine temperature, vibration, and fuel-consumption data fed into a machine-learning model.

Alerts go to the maintenance team before predicted failure.
Models learn from your own service history.
Confidence scores help engineers decide what to inspect first.

Connected to your stack

Works with the systems your team already uses.

Tan & Co. connects planning data without forcing a replacement project. Onboarding includes dispatcher training and a measured pilot.

SAP TMTransport planning integration

Oracle TMSOrder and route data

CargoWiseFreight workflow connection

LogisysFleet planning data

SamsaraVehicle telemetry

GeotabGPS and driver data

AIS dataVessel movement signals

digitalPORT@SGPort community systems

Planning estimate

See what fewer wasted kilometres could mean.

Move the figures to model a starting point for your fleet. This estimate uses a 22% reduction in fuel cost, based on a regional trucking result.

Fleet size50 vehicles

Daily distance per vehicle180 km

Current monthly fuel spend$45,000

Estimated annual fuel saving $118,800 Actual results vary by fleet, route mix, fuel price, and operating policy.