Case study 01 · Logistics & Supply Chain
Scalable logistics platform
A coordination layer for orders, inventory and partner handoffs when exception handling was still tribal knowledge.
- Challenge
- Physical operations ran across operator tools, partner APIs and spreadsheets. Failures were handled in chat. The software was only useful if it made TAT, handoffs and exceptions visible.
- Architecture
- Bounded services for orders, inventory, partners and exceptions, with an API façade over existing systems of record and queues in front of bursty partner traffic.
- Engineering
- Idempotent partner callbacks, dual-run during cutover, and observability on exception age and TAT — so operators could act before a lane became a pile-up.
- Outcome
- Operators worked from one exception surface. New partner integrations could be added without rewriting the core movement path.
Problem
A logistics operation had grown faster than its software. Orders, inventory and partner status lived in different tools. When a handoff failed — a missed pickup, a stock mismatch, a partner timeout — the recovery path was a person in a group chat. Leadership wanted a platform. Operators needed the exceptions to stop disappearing.
Context
The existing systems of record could not be switched off. Carriers, warehouses and internal teams already depended on them. A rewrite would have paused physical operations. The work was to put a coordination layer in front, then move capability across without a single cutover.
Users
Hub and warehouse operators who live in exceptions, not dashboards. Partner managers who need a contract they can reason about. Internal product teams who had been rebuilding the same order and inventory logic for every channel.
Constraints
Partner APIs were unreliable and bursty. Some events arrived twice; some never arrived. Inventory numbers had to stay consistent enough to promise a shipment. Change windows were operational, not only technical. Data residency and access for third-party operators had to be explicit.
Architecture
Orders, inventory, partners and exceptions became separate services with explicit APIs. An API façade wrapped the current systems of record so clients did not couple to them. Queues absorbed partner bursts and retries. A thin operator console sat on the exception service — the surface people actually used when something broke.
Technology
Event-driven services, a contract-first API layer, and an integration bridge rather than point-to-point partner calls. The data model treated an exception as a first-class entity with owner, age and next action — not a log line. Observability was designed around TAT and queue depth, not only HTTP success rates.
Engineering challenges
Idempotency on partner callbacks. Ordering when inventory and shipment events raced. Dual-run against the old tools so operators could compare before cutover. Defining “done” for an exception so the queue did not become another inbox. Keeping the façade honest when the underlying system still had undocumented side effects.
Solution
We shipped the façade and exception surface first, then moved order and inventory writes across service by service. Partner integrations went through one bridge with retries, dead-letter handling and a replay path. Cutover criteria were operational: operators could close exceptions in the new console without a shadow spreadsheet.
Outcome
Exception handling moved out of chat and into a system with an owner and an age. Partner onboarding became an integration against a stable contract. The core movement path could change without pausing the network. The platform is still evolving — that was the point of not betting on a rewrite.
Lessons
In logistics, the architecture is the exception path. Happy-path order models look complete until a partner times out at 2 a.m. Dual-run is slower to start and faster to trust. Operator consoles are not a reporting afterthought; they are how the system earns the right to exist.
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