Ortec introduces AI-based optimisation in delivery operations for e-grocery

Ortec, a company specialising in supply chain planning and workforce management, has announced new functionality for delivery operations in the e-grocery sector through the Ortec for Home Delivery (Ohd) suite.

The platform combines artificial intelligence-based optimisation, advanced analytics and integrated planning to help grocery retailers improve delivery performance, reduce costs and address the growing complexity of the last mile.

With demand for online grocery shopping continuing to grow, retailers must ensure increasingly fast and reliable deliveries while also addressing rising transport costs, demand volatility and ever tighter delivery windows. Ortec responds to these challenges by integrating optimisation directly into daily planning and execution processes, enabling companies to move from a reactive approach to continuous, data-driven operations.

The technology

At the heart of Ortec’s e-grocery solution are dynamic order allocation and delivery time-window optimisation, which constantly adapt as new orders arrive. Instead of relying on static planning cycles, retailers can manage deliveries as a continuous process, adjusting decisions in line with changing demand and operational constraints.

The platform enables operational efficiency and customer experience to be balanced through the dynamic management of delivery and collection windows, the allocation of orders between proprietary fleets and gig-economy networks, and the real-time optimisation of routes, labour and supplies. The management of areas and time slots also makes it possible to differentiate the offering for B2c, B2b and other customer segments with specific service levels, while maintaining available capacity for priority customers.

Customer nudging

Another element is the so-called customer nudging, which guides consumers towards more efficient delivery windows through dedicated incentives, increasing slot utilisation and reducing last-mile costs.

For store-based order fulfilment models, Ortec coordinates picking capacity, delivery-window availability and the management of service areas. Forecasting models help align store resources with actual demand, identifying when to increase order-preparation capacity to capture additional sales opportunities and ensure high service levels.

The algorithms

The solution combines advanced optimisation algorithms and machine learning to continuously improve planning accuracy and execution reliability. The models learn from historical data relating to on-time deliveries and operational performance, refining parameters such as travel times, stop durations and available capacity. The routing algorithms also integrate real-time traffic and road-network data, enabling an immediate response to new orders or unforeseen events without manual intervention.

Integration with Erp, Wms and transport platforms ensures that planning decisions can quickly be translated into operational activities, reducing information silos and accelerating responses to events. To support execution, mobile applications for drivers are available with guided workflows and proof-of-delivery functionality, while customers receive real-time updates on estimated arrival times and proactive notifications in the event of delays.

Ortec also supports sustainability objectives through the intelligent allocation of electric vehicles. By forecasting energy requirements for each route, retailers can maximise the use of EV fleets and reduce the risk of disruptions related to battery limitations.

The commentary

"As e-grocery evolves, retailers need much more than fast deliveries: they require effective control over increasingly complex operations," said George Ninikas, senior vice president sales and accounts at Ortec. "Our solutions apply artificial intelligence where it delivers tangible results, optimising routes, capacity and delivery planning while taking real-world constraints into account. In this way, retailers can build operations that are more efficient, resilient and ready to grow."

The company also announced the platform’s evolution towards an agentic AI approach, which will integrate increasingly autonomous and proactive decision-making capabilities into workflows. According to George Ninikas, Ohd will progressively be able to support retail teams as a true operational copilot, reliably and controllably automating well-defined decisions.

This article was translated from the original Italian version with the assistance of artificial intelligence. In case of discrepancies, please refer to the original Italian version.