A distribution business went from tracking forty vehicles on a whiteboard to running its entire dispatch operation in real time.
A distribution business went from tracking forty vehicles on a whiteboard to running its entire dispatch operation in real time.
A family-run distribution business in Lagos — forty vehicles, sixty drivers, two decades of trust — was growing faster than the systems that ran it.
They came to us with what sounded like a simple request: “we need an app to track our trucks.” The brief we actually took on was bigger — give the whole operation eyes.
A family-run distribution business in Lagos, moving goods for retailers across the south-west.
Forty vehicles, sixty drivers, and a reputation built over two decades on getting orders where they needed to be. The business was growing — new clients, more routes, bigger volumes. But the systems that ran it hadn’t grown with it. When they came to us, dispatch was still being coordinated the way it had been when the fleet was a tenth the size.
No one could see the state of the operation at any given moment. A dispatcher held it in their head, on a whiteboard, and across three phones.
When a driver was late, the office found out when the customer called angry. Every Friday vanished into reconciling delivery notes by hand — finding the errors only after they’d already cost money. We’d met this exact shape of problem before: it isn’t a tracking problem, it’s a visibility and coordination problem.
Before: 3 hours per order fulfillment. Manual. Error-prone. Invisible.
The request that came in was “we need an app to track our trucks.” That’s not the problem we built for.
The real problem was that no one could see the state of the operation at any given moment. A dispatcher held it in their head, on a whiteboard, and across three phones. When a driver was late, the office found out when the customer called angry. When a vehicle broke down, re-routing meant calling around to see who was free. Every Friday was spent reconciling delivery notes by hand — and finding the errors after they’d already cost money.
We’d seen this exact shape of problem before. It isn’t a tracking problem. It’s a visibility and coordination problem, and an app that only shows dots on a map would have solved almost none of it.
Before: 3 hours per order fulfillment. Manual. Error-prone. Invisible.
A record of the decisions that shaped the build — and why we made each one the way we did.
We built a relational database rather than a spreadsheet-based system because their business relationships were genuinely complex, and data integrity was non-negotiable. A spreadsheet would have looked cheaper on day one and failed within eighteen months as the cross-references multiplied.
We designed the approval workflow in three steps rather than one because the ops team reviews dispatches on mobile, out on the floor — and one-step forms on small screens carry a 34% higher error rate in the field.
Drivers spend their day in areas with unreliable mobile coverage. The driver-facing app is offline-first: records deliveries locally and syncs the moment a connection returns. A connected-only app would have been useless exactly when it mattered most.
Every vehicle, driver, and order in one real-time view that updates on a four-second poll.
Records deliveries with no connection and syncs automatically when signal returns.
Delivery records reconcile themselves — no more Friday spent hunting for errors.
| Vehicle | Driver | Route | Status | ETA |
|---|---|---|---|---|
| TRK‑041 | A. Bello | Ikeja → Lekki | en route | 14 min |
| TRK‑019 | C. Okeke | Depot | loading | — |
| TRK‑077 | M. Sani | V.I. → Yaba | en route | 31 min |
| TRK‑004 | J. Eze | Apapa → Ikeja | delayed | 52 min |
| TRK‑052 | K. Adamu | Surulere | en route | 9 min |
They understood our business before they wrote a line of code. The software just made that understanding run by itself.
Tell us about the business problem. We’ll tell you if we’re the right fit.
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