Freight Broker's AI Agents Chase Missed Pickups
Quick Summary
C.H. Robinson uses a pair of AI agents to find and resolve missed less-than-truckload pickups. One agent calls the carrier, the other decides what to do next. The agents now handle 95% of missed-pickup checks and save more than 350 staff hours a day.
The Use Case
When an LTL carrier misses a pickup, the freight sits, another truck has to come back the next day, and other shippers' loads get delayed. Teams of people spent over half their day checking carrier websites, calling terminals and recording updates. C.H. Robinson built two agents that split the job: a calling agent that phones carriers about missed pickups, and an analysis agent that reads the situation and picks the resolution. They work around 100 calls and decisions at the same time. The missed-pickup data is also shared with carriers every day, so carriers can fix the scheduling and terminal problems that caused the misses in the first place.
Real Example
- The system spots a pickup that was scheduled but not confirmed by the carrier
- The calling agent phones the carrier terminal and asks about the status
- The analysis agent reads the answer, determines whether the freight was picked up, rescheduled or missed, and decides the resolution
- The shipment record is updated and the customer is notified, with no person in the loop
- Cases outside the agents' rules are handed to a human rep with the call context attached
- Each day the missed-pickup data is compiled and sent to carriers to fix root causes
Why It Matters
- 95% of missed-pickup checks are now automated
- More than 350 manual hours saved every day across the team
- 42% fewer unnecessary return trips, and freight moves up to a day faster