Real-time data pipeline for a logistics operator

The client is a German logistics operator whose many teams all needed the same track-and-trace event data, but each was fetching it their own way. Consistent, timely parcel status underpins both operations and customer promises.

Teams were building their own batch extracts, so the same data arrived hours stale and subtly different depending on who you asked.

Teams each built their own batch extracts, so parcel status was hours stale and subtly different depending on who you asked. The same reality was being represented inconsistently across the business.

That fragmentation undermined operational decisions and customer promises alike. Acting on stale, inconsistent data has real operational cost.

The operator needed one real-time, consistent source of track-and-trace events for the whole business. A single, current, governed stream was the goal.

We built a streaming backbone with a shared event store, so teams subscribe to governed real-time data instead of rolling their own extracts. A shared stream replaces many divergent copies with one source of truth.

Schema contracts govern every event, so a producer change cannot silently break downstream consumers. Contracts turn a fragile web of extracts into a stable, evolvable platform.

Sub-second delivery meant parcel status reflected reality as it happened, and we onboarded teams onto the stream progressively, retiring the duplicated batch jobs as we went. The consolidation happened without disruption.