ULAX

ULAX addresses key challenges in urban last-mile delivery: rigid tour planning, short-notice ad-hoc orders, heterogeneous delivery models, complex driver interfaces, and fragmented IT systems. The project develops an AI-based SaaS system that combines planned tours, recurring milk runs, pick-up and drop-off points, smart lockers, and same-day or ad-hoc deliveries within one adaptive control logic.

The core component is a driver-focused AI agent. It continuously processes delivery, vehicle, sensor, traffic, weather, and environmental data and dynamically adapts route and tour recommendations. Drivers receive context-aware, multilingual guidance on mobile devices or in the vehicle, including route changes, delivery priorities, ETA updates, and next actions. This reduces dependence on local knowledge and lowers the onboarding barrier for new drivers.

ULAX also creates a digital twin of the parcel journey. Events from goods receipt through loading, transport, parking, walking delivery, and final handover are documented and made available for analysis. Historical delivery data is used to train AI models so future routes can be optimized based on previous experience. Dispatchers receive a monitoring dashboard with real-time visibility into utilization, status, deviations, and process quality.

In cooperation with Rytle Mobility GmbH and Orbitak AG, the project combines logistics process expertise, micromobility and sensor integration, cloud software, API connectivity, and AI-based optimization. Funded by Bremer Aufbau-Bank GmbH (BAB), ULAX aims to increase operational efficiency, transparency, and delivery quality while reducing unnecessary mileage, delays, emissions, and resource consumption in urban logistics.