Logistics & Supply Chain
Route optimization, WMS platforms, carrier integrations, and real-time visibility systems: built by engineers who understand that downtime in logistics isn't abstract.
Where logistics engineering fails
Shipment tracking, inventory levels, and vehicle location need to be accurate in near-real time. Stale data in logistics leads to customer calls, missed SLAs, and expensive re-routing.
Carriers, 3PLs, customs brokers, ERP systems, and customer portals all need to talk to each other. Each integration has its own data format, authentication method, and failure mode.
Vehicle routing, load optimization, and network design are NP-hard problems. Good solutions require the right algorithms and the data quality to feed them.
Delays, damages, lost parcels, address corrections, and customs holds are the norm, not edge cases. Software that only handles the happy path creates more work for operations teams.
What we build
Warehouse management systems, pick/pack/ship workflows, slotting optimization, and inventory accuracy tooling.
Real-time tracking APIs, customer notification systems, proof-of-delivery workflows, and exception management dashboards.
FedEx, UPS, USPS, DHL, and custom carrier EDI integrations. Engineers who've built reliable rate shopping, label generation, and tracking ingestion systems.
AI in this industry
Demand forecasting, dynamic routing, and predictive maintenance are the most impactful AI applications in logistics right now. The models aren't the hard part: it's the sensor data quality, the real-time data infrastructure, and the integration with existing dispatch and ERP systems that determine whether a forecast is useful in production.
Common tech stack
Python
Node.js
Java
Go
Kafka
PostgreSQL
Redis
AWS
GCPFAQ
We'll find engineers who understand the difference.
