Do you have engineers with route optimization experience?

Yes: specifically with OR-Tools, OSRM, and custom VRP solver implementations. This is a niche but not rare in our network. We ask about algorithm complexity and real-world constraints during vetting.

Can you help with EDI integrations for carriers and 3PLs?

EDI experience is in our network, though it's a narrower pool. We're transparent about it: tell us the specific transaction sets and trading partners involved and we'll give you an honest assessment.

What about real-time tracking systems at scale?

We've placed engineers on high-throughput event streaming systems using Kafka and WebSocket-based tracking. The key questions are event volume, update frequency, and the customer-facing latency requirements.

Logistics & Supply Chain

When engineering failures cost money by the hour.

Route optimization, WMS platforms, carrier integrations, and real-time visibility systems: built by engineers who understand that downtime in logistics isn't abstract.

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Where logistics engineering fails

Logistics systems have to be right, not just fast.

Real-time data is essential, not nice-to-have

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.

Integration surface is enormous

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.

Optimization problems are genuinely hard

Vehicle routing, load optimization, and network design are NP-hard problems. Good solutions require the right algorithms and the data quality to feed them.

Exceptions outnumber the happy path

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

Specific capabilities for logistics engineering teams.

5 use cases

Route optimization and dispatch

VRPTW solvers, multi-stop route optimization, and real-time re-routing systems. Engineers who understand the tradeoffs between solution quality and compute time.

WMS and warehouse systems

Warehouse management systems, pick/pack/ship workflows, slotting optimization, and inventory accuracy tooling.

Last-mile tracking and visibility

Real-time tracking APIs, customer notification systems, proof-of-delivery workflows, and exception management dashboards.

Carrier and 3PL integrations

FedEx, UPS, USPS, DHL, and custom carrier EDI integrations. Engineers who've built reliable rate shopping, label generation, and tracking ingestion systems.

Supply chain analytics

Demand forecasting, inventory optimization, carrier performance analytics, and operations dashboards. Built on clean data pipelines, not spreadsheet exports.

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