Industry
Supply chain and logistics solutions for inventory management and delivery optimization
12 solutions
Algorithms that compute the most efficient delivery routes across vehicle fleets — minimising distance, fuel, and driver hours while respecting time windows and load constraints.
Forecasting models that predict demand at warehouse locations to set optimal replenishment triggers — reducing both excess inventory holding costs and stock-out events.
Telematics platforms that collect GPS, engine, and driver behaviour data in real time — providing visibility into fleet location, utilisation, fuel consumption, and driver safety.
WMS systems and automation logic that direct picking, packing, putaway, and replenishment — optimising labour allocation, slot assignments, and throughput in complex warehouse environments.
End-to-end platforms that aggregate data from suppliers, carriers, and distribution nodes — providing unified inventory position, order status, and delay prediction across the supply chain.
Analytics applied to dock scheduling, carrier selection, mode optimisation, and labour planning — reducing cost per shipment and improving service levels without adding headcount.
RPA and workflow automation for repetitive logistics tasks — purchase order creation, carrier booking, freight invoice reconciliation, and proof-of-delivery matching.
Network-level analytics for freight operators that model fleet productivity, load factor, empty miles, and driver scheduling across regional and national transport networks.
LLM applications that help supply chain planners analyse disruption scenarios, summarise supplier reports, draft RFQs, and query operational data through natural language.
Full-stack engineering of TMS, WMS, freight marketplace platforms, and last-mile delivery applications — built for the reliability and throughput of millions of daily shipments.
Advisory engagements that audit logistics network data maturity, identify the highest-value AI use cases, and deliver a phased implementation roadmap with commercial validation.
IoT and ML systems fitted to commercial vehicles that predict mechanical failures from engine telemetry — enabling proactive service before a breakdown disrupts operations.
