From predictive fleet maintenance 48 hours before breakdown to AI-optimised routing, autonomous depot orchestration, and smart rail management — TechProf delivers transport AI that cuts operating costs, improves safety, and reduces emissions. Running live across road, rail, and logistics estates.
From the vehicle to the depot to the control room — AI that runs the full transport operation more efficiently, more safely, and with dramatically lower emissions than legacy approaches.
Transport AI must work in the field — in depots with intermittent connectivity, on vehicles with constrained compute, and in control rooms that need decisions in seconds. TechProf's transport systems are architected for edge deployment, with cloud-based optimisation models that sync back in real time when connectivity allows.
Our fleet intelligence platform ingests CAN bus data, GPS telemetry, tachograph data, and third-party traffic feeds — producing maintenance predictions and route decisions that survive real-world operating conditions.
Real systems running in live transport operations — from national road fleets to urban transit authorities and rail franchises.
Fleet intelligence platform deployed across 847 HGVs for a national logistics operator. CAN bus telemetry, tyre pressure, and brake wear sensors feed a predictive model that flags maintenance needs 48 hours before breakdown. Unplanned downtime reduced by 67%.
Real-time routing AI for a B2C delivery operator — 2,200 vehicles across the UK. Live traffic, weather, demand patterns, and vehicle capacity integrated into continuous route recalculation. Fuel consumption down 12%, customer on-time delivery up to 98.4%.
AI-driven depot management platform — load planning, dock slot allocation, driver scheduling, and EV charging optimisation for a 12-depot national network. Throughput increased 23%, overtime reduced by 31%, and EV charging costs reduced by 38%.
Capacity prediction and service disruption management for a UK Train Operating Company. AI forecasts demand by station, time, and service — adjusting rolling stock allocation and managing disruptions autonomously. Passenger satisfaction up 18%, delay compensation down 44%.
In-cab AI platform using computer vision to detect fatigue, distraction, and unsafe driving behaviour across a coach fleet. Real-time alerts to drivers and fleet managers. Incident rate reduced by 52% in the first year. Fully compliant with GDPR and tachograph regulations.
End-to-end supply chain visibility platform for a 3PL operator — real-time shipment tracking, exception management, and autonomous rerouting when disruptions occur. Customer portal with live ETA updates reduced inbound enquiry volume by 61%.
A structured delivery model built around the operational realities of transport — legacy telematics, driver data, depot workflows, and regulatory compliance baked in from day one.
Assess your existing telematics, maintenance data, routing systems, and depot workflows. Identify quick-win automation opportunities and long-term AI integration points across the operation.
Target architecture designed for the realities of transport — edge-deployed models that work offline, cloud sync when connected, and integrate with existing TMS, WMS, and fleet management systems.
Depot-by-depot or route-by-route deployment — building confidence through measured results before expanding. Driver training and change management embedded in the programme from day one.
24/7 fleet intelligence with autonomous anomaly detection, model retraining as your fleet evolves, and regular operational reviews to expand AI coverage across the estate.