Portfolio

Distributed fulfillment network that matches merchant inventory to fulfillment nodes based on proximity, capacity, and service-level constraints — letting mid-market e-commerce brands achieve 2-day delivery without owning a single warehouse.

Predictive ETA platform for ocean freight. Ingests vessel position data, port congestion signals, and carrier schedules to produce probabilistic arrival forecasts — replacing the static ETD/ETA fields that forwarders have relied on for decades.

Shipment visibility and customer portal that freight forwarders deploy under their own brand. Forwarders stop losing accounts to brokers with better tracking UX — their shipper customers get real-time milestone updates and exception alerts without the forwarder building software.

Digital freight forwarding platform for SME importers and exporters. Rate comparison and carrier selection backed by historical lane performance data, compressing procurement cycle times that previously required broker relationships and manual RFQ rounds.

Shipping decision engine that evaluates carrier selection, service-level options, and zone-skipping logic at checkout latency — making the call that a human logistics manager would make in an afternoon, in milliseconds per order.

Load planning engine for full-truckload carriers. Uses reinforcement learning to make driver dispatch and load assignment decisions that account for regulatory hours-of-service constraints, repositioning costs, and backhaul opportunities — replacing the planner who ran these calls from a whiteboard.

Shared execution layer for shippers, carriers, and brokers. When a load misses a pickup window or a driver goes dark, all parties see the exception at the same time and can act from the same record — reducing the phone-tag that defines most freight exception management today.

Decision engineering platform for routing, scheduling, and allocation problems in supply chains. Lets engineering teams build, run A/B tests against, and deploy decision models without requiring an in-house operations research function — the OR talent gap that blocks most mid-market logistics operators.

Returns intelligence platform that scores return probability at checkout, routes returned items to the highest-margin disposition channel — resale, refurbishment, liquidation — and tracks the actual cost of return by SKU and origin region.

Last-mile route intelligence for urban delivery operators. Combines real-time traffic feeds with ML-based time-window and access-constraint prediction to cut failed first-attempt deliveries — the cost that makes urban last-mile economics brutal at scale.

Computer vision monitoring layer for material recovery facilities. Classifies waste stream composition in real time on conveyor belts, giving sorting operators the throughput and contamination data they need to optimize recovery rates and comply with EU packaging regulation reporting.

Cognition layer that runs above an existing WMS. Applies ML to slotting decisions, pick-path optimization, and inbound flow prediction — improving throughput and labor utilization without requiring operators to rip out the legacy system they've spent years configuring.

Procurement intelligence platform that builds a learning model of supplier behavior from every sourcing event — price sensitivity, lead-time variability, quality deviation patterns. Over time the model makes a new buyer as informed as a ten-year category manager.