Modernising logistics across East & Southern Africa.
Logistics AI that works here orchestrates partners, corridors and exceptions — it does not pretend roads are autonomous. Operators that win fix tracking and POD truth, forecast with sparse data, then route and exception-manage.
EdgeTech Logistics practice — operable systems for African corridors.
Why logistics AI stalls — and what unsticks it.
Corridors here mix formal fleets, informal agents, border friction and patchy connectivity. Importing predictive platforms trained on dense Western networks produces ETAs field teams ignore.
The guides below stay on that reality: last-mile operations, predictive honesty, rejecting leapfrog autonomy, orchestrating partners, forecasting sparsely, and refusing black boxes.
Logistics, guide by guide.
Last-mile in East Africa
Beyond basic tracking to operable delivery.
Read the guidePredictive hype → reality
What African corridors actually need from AI.
Read the guideMyth of autonomous leapfrog
Why driverless last-mile is the wrong near-term bet.
Read the guideOrchestration over automation
Coordinating partners beats black-box robots.
Read the guideDemand forecasting
Forecasting with sparse, noisy African demand data.
Read the guideReject the black box
Explainable logistics decisions operators can trust.
Read the guideSystems operators will run on a bad road day.
We design and build tracking, exception and forecasting tooling that fits East and Southern African operating reality.
EdgeTech Logistics Practice
Last-mile · Orchestration · Forecasting · since 2014
Questions we get asked.
Is autonomous last-mile realistic in East Africa?
Where should a 3PL start with AI?
How do you forecast with sparse demand data?
What does EdgeTech build for logistics?
Shape a logistics brief.
Last-mile, forecasting or orchestration stuck? We build for the corridor you have.