Webinar Description

What if your routes could learn from every delivery?

In this AI Exchange session, we will explore how moving beyond static service time assumptions unlocks a new level of fleet performance. Traditional routing treats each stop as predictable but, in reality, each one is shaped by order size, product mix, site conditions, unloading requirements, and crew readiness. AI and machine learning change the model by learning from actual delivery behavior and continuously applying that intelligence to future routes.

At the same time, performance does not stop at planning. Real time communication keeps dispatch, drivers, and customers aligned with accurate ETAs, proactive updates, and shared visibility, helping teams stay coordinated and reduce unnecessary check-ins.
 

What you will take away:

• How increased precision can drive up to 30% more route density without adding trucks or drivers
• How static service time assumptions hold back route accuracy and fleet performance
• How AI-driven service times adapt to real world variability across every stop
• How learning from actual delivery behavior improves planning over time
• How real time visibility and communication support stronger execution in the field 

Speakers:

Cyndi Brandt, Vice President, Fleet Solutions, Descartes
Sergio Torres, Senior Vice President, Product Management, Descartes   

Moderator:

Robert Bowman, Editor-in-Chief, SupplyChainBrain