Software built and proven for logistics, where a sync failure becomes a truck in the wrong place.
Warehouse management, route optimisation, freight visibility and last-mile tracking, built for systems where state drifting out of sync has a physical consequence.
What building for Logistics actually requires.
Logistics software models the physical world, and the physical world disagrees with it constantly. A pallet is moved without a scan, a delivery is refused, a vehicle breaks down. The system's job is to reconcile rather than to assume its own record is correct.
Timing is a correctness property. A route optimised against stale traffic or capacity data is wrong even though every calculation was right, so freshness guarantees matter as much as the algorithm.
Integration count is unusually high. Carriers, customs, warehouse hardware, telematics and customer systems each have their own formats, reliability and outage behaviour, and the platform is judged on how it behaves when one of them is down.
Where it breaks without care.
Inventory and shipment state are updated optimistically, so a failed downstream call leaves the record and the physical reality permanently diverged.
Route and capacity logic is tested on clean fixtures rather than on real exceptions: failed deliveries, partial loads, address corrections and vehicle substitutions.
Carrier integrations are tested only against their sandbox, so real-world rate limits, malformed responses and outages are discovered in production.
Peak-season load is modelled as a uniform multiple of average traffic, which misses the sharp concentrated spike that actually breaks scanning and tracking endpoints.
How we deliver it.
Idempotent state transitions with explicit reconciliation, so a retry or a failed downstream call cannot leave inventory and reality diverged.
Route, capacity and slot logic exercised against real exception data rather than clean fixtures, since exceptions are the majority of the interesting cases.
Carrier and customs integrations tested under rate limiting, malformed responses and outage, with defined degradation for each.
Peak testing modelled on the true seasonal shape, including the concentrated opening spike, not an evenly scaled average day.
Offline-tolerant scanning and driver apps, because warehouses and delivery routes both contain places with no signal.
Industry focus areas.
Warehouse management
Route optimisation
Freight visibility
Last-mile tracking
Carrier integration
Customs & documentation
Evaluating a build partner?
A two-week scoping engagement covering architecture review, risk mapping specific to logistics & supply chain, and a 90-day delivery plan across build and quality engineering. You keep the plan whether or not you continue with us.
Logistics questions, answered.
What breaks most often in logistics platforms?
State divergence between the system and physical reality, usually caused by optimistic updates that are never reconciled after a downstream failure. It surfaces as inventory that does not match the shelf.
How do you test route optimisation?
Against real exception data, not clean fixtures: failed deliveries, address corrections, partial loads and vehicle substitutions. Optimisers usually behave well on tidy input and badly on a real day.
Can you prepare a platform for peak season?
Yes, and the shape of the test matters. We model the actual seasonal profile including the sharp opening spike, because an evenly scaled average day does not reproduce what breaks.
Built for Logistics,proven before launch.
Senior engineers who know where this sector breaks, and the quality engineering to prove your build does not.