Live fleet tracking
Every one of the 5,000 vehicles on a single map, refreshing in sub second time so the floor always sees the present, not the past.
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Logistics
A Saudi logistics operator
When this Saudi operator first walked us through their day, the picture was familiar but the scale was not. Vision 2030 demand had pushed their fleet past 5,000 vehicles, and they were still coordinating all of it the way they had at a few hundred trucks. Dispatchers worked off spreadsheets and a radio handset. If a driver went quiet, nobody knew whether he was stuck in Riyadh traffic, sitting at a closed loading bay, or simply done for the day. The operations floor had grown loud and reactive, and the people running it were exhausted by the guesswork.
The cost of that blindness showed up everywhere. Routes were drawn by hand each morning, so trucks doubled back across the city and burned fuel they did not need to. When a customer called asking where their delivery was, the honest answer was that nobody could say. Fuel was the largest controllable line in the budget and it kept climbing, but without live data there was no way to prove where the waste was hiding, let alone stop it.
| Before | After | |
|---|---|---|
| Fleet visibility | Spreadsheets and a radio handset | Every vehicle on one live screen |
| Route planning | Drawn by hand each morning | Optimised automatically for traffic and time windows |
| Fuel use | Climbing with no way to trace waste | Down 18 percent across the fleet |
| Late deliveries | Piling up through every peak | Down 22 percent with accurate ETAs |
The peak seasons made it impossible to ignore. During a promotional surge the volume roughly doubled, and the manual process simply buckled. Dispatchers were planning the next wave of routes while the current one was still falling apart, late deliveries piled up, and the radio never stopped. Leadership realised they were not short on trucks or drivers. They were short on visibility. Every decision was being made minutes too late, on information that was already wrong by the time it reached the floor.
We built a custom operations platform around one idea: put the whole fleet on one live screen, then let the software do the planning that humans were doing by hand. Telematics from all 5,000 vehicles flows into an event driven backend that we sized for the worst day, not the average one, so the promotional spikes that used to break the old process now pass through without drama. On top of that live picture sits a routing engine tuned to the operator's real constraints rather than a generic optimiser.
Every one of the 5,000 vehicles on a single map, refreshing in sub second time so the floor always sees the present, not the past.
An engine that plans the day against real traffic, delivery windows and vehicle capacity instead of forcing the operation into a generic template.
When a truck drifts off plan or a window is at risk, a dispatcher hears about it the moment it happens rather than from an angry phone call later.
Accurate arrival times and proof of delivery capture, so customers watch a live countdown instead of dialling the operations floor.
An event driven pipeline sized for the worst day of the year, so promotional peaks that once doubled volume pass through without strain.
Built for 99.9 percent uptime, because a logistics floor that loses its screen is back to the radio and the guesswork.
The first thing dispatchers noticed was quiet. With every vehicle on screen, the radio stopped being the nervous system of the operation. The harder numbers followed. Smarter routing took fuel consumption down 18 percent across the fleet, which on a budget that size is the kind of saving that pays for the build many times over. Planning around real time windows meant 22 percent fewer late deliveries, and the customers who used to phone in now just watched an accurate ETA tick down.
One moment early in the rollout told us the platform had landed. We had spent two weeks sitting beside the dispatchers, watching how they actually worked rather than how a manual said they should, and the most senior of them was the most sceptical. He had run that floor on instinct for a decade. Then a major loading bay closed without warning during a busy afternoon, and instead of the usual scramble he simply rerouted the affected trucks from his screen in a couple of minutes, never reaching for the radio once. He turned to our engineer, half surprised at himself, and said the floor had not felt that calm in years. After that the team stopped treating the software as our project and started treating it as theirs.
vehicles tracked live
less fuel
fewer late deliveries
platform uptime
The payback
On a fuel budget that size, an 18 percent cut paid back the cost of the build many times over inside the first year.
For years I planned routes on a whiteboard and prayed the traffic agreed with me. Now I open one screen in the morning and the system has already worked out the day. The first month, our fuel bill dropped enough that the finance team asked me what we had changed. That has never happened to me before.— Operations Director, a Saudi logistics operator
Illustrative figures
Client identity is anonymised and the figures shown are illustrative of the outcomes this kind of platform delivers.
FAQ
We leaned on an event driven design with a Kafka streaming pipeline and Redis caching. Position and status updates from the whole fleet land on the dispatcher dashboards with sub second latency, and that holds true even during the promotional peaks when volume roughly doubles.
Custom built. Off the shelf tools forced the operation into their assumptions, so we wrote an engine tuned to the operator's actual constraints, including vehicle capacity, delivery time windows and regional traffic patterns, rather than the other way round.
The live visibility paid off almost immediately once every vehicle was on one screen. The fuel saving of 18 percent and the 22 percent drop in late deliveries built up over the first full quarter as the routing engine learned the real traffic and time window patterns across the network.
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