Why did routes run long this week? Which drivers are trending toward overtime? Where are service levels at risk? These are just some of the questions dispatchers can ask Descartes Systems Group’s new AI agent, René.
Descartes launched René to change the way fleets use the massive amounts of data they generate daily – or rather to urge fleets to execute on their data that often goes unused. René is part of the new Descartes Fleet Data Intelligence platform, built on the operational data of its Global Logistics Network (GLN).
For fleets operating private or dedicated distribution networks, the highest-impact opportunity for AI lies in improving real-world execution, said James Wee, general manager of fleet management at Descartes.
“Execution data contains the signals needed to enhance fleet performance but, historically, it hasn’t been fully leveraged,” he said. “With the Fleet Data Intelligence platform, we apply AI to the trusted execution data flowing through the GLN to separate signal from noise and turn everyday fleet operations into a continuous source of learning and improvement.”
The platform combines the new AI agent and machine learning (ML) capabilities to enhance on-time delivery, strengthen service level compliance and reduce cost per delivery while providing the visibility needed to measure, sustain and scale fleet performance improvements over time.
René surfaces both real-time insights and longer-term improvement opportunities without requiring manual data extraction or specialized analytics expertise. It enables planners, dispatchers and operations leaders to investigate issues, test hypotheses and get immediate answers simply by asking questions like those previously mentioned. It also uncovers deeper, systemic patterns by analyzing large volumes of fleet execution data to identify trends and unearth root causes of inefficiencies such as a group of drivers consistently logging excess miles due to manual route deviations.
The platform’s ML capabilities have increased route density by up to 30% in early deployments, enabling fleets to complete more stops without adding vehicles or drivers. It generates more accurate service time predictions by learning from real-world delivery durations and route conditions across variables such as customer type, product characteristics, delivery volume, vehicle type, charging stop locations and geography. Improved planning precision minimizes excess buffer time, idle capacity, missed delivery windows and route plans that diverge during execution, allowing companies to schedule more stops per driver within the same working hours.
The platform also delivers visibility into key performance metrics for benchmarking in areas like route efficiency, service compliance and driver productivity so fleets can validate results, reinforce best practices and scale performance gains across their operations.
The latest acquisition
Descartes Systems Group has also added predictive safety intelligence to its GLN with its acquisition of Idelic, a provider of AI-powered driver safety and performance management solutions.
The Idelic platform unifies day-to-day safety management activities, from training and monitoring to reporting and coaching, into a single solution. The platform helps fleets identify and reduce driving risk by leveraging its dataset of more than 40 billion miles of telemetry and over 400,000 accident records. Idelic collects real-time, event-level data through a connected network of more than 80 telematics, risk management and regulatory system integrations.
Descartes closed the transaction with an up-front consideration of $28 million in a deal that the company said will strengthen its fleet management and final-mile capabilities.
