How C.H. Robinson Automates 5,500 Shipments Daily with LangChain AI Agents
C.H. Robinson, one of the world's largest logistics providers managing 37 million shipments annually, built AI agents using LangChain and LangGraph to automate email-based shipment orders end-to-end. The platform now processes approximately 5,500 orders per day automatically, saving more than 600 hours of manual email processing work daily.
Impact
~5,500
Orders automated daily
600+ hours
Manual processing time saved per day
15,000
Emails received per day
~7 minutes
Previous processing time per email
Up to 4 hours
Previous queue wait time
Challenge
C.H. Robinson received 15,000 shipment-related emails daily from customers who still transact via email, each requiring 7 minutes of manual processing to interpret inconsistent formats, classify load types, fill missing data, and create orders — creating significant queue delays and operational cost.
Solution
C.H. Robinson's GenAI team built LangChain-powered AI agents to automate the full email-to-order workflow, using LangGraph for stateful classification of complex shipment types and LangSmith for pre-deployment observability and ongoing performance monitoring.
Tools & Technologies
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Full Story
C.H. Robinson connects shippers and carriers across every mode of transport — truck, rail, ocean, and air — for 83,000 customers worldwide. Its scale is substantial: 37 million shipments per year, routed through a global network that spans every major trade lane. The company invested heavily in digital ordering tools, but a structural challenge remained: a significant portion of its customer base still transacts via email. Every day, 15,000 emails arrive containing shipping requests in wildly inconsistent formats — handwritten PDF notes, scanned documents, partial requests missing key fields, and everything in between.
Each email required a human agent to read, interpret, classify (less-than-truckload versus full truckload is a consequential distinction in freight pricing), fill in missing data, create the order, schedule appointments, and initiate tracking. The average processing time was seven minutes per email, with some batches waiting up to four hours in queues. At 15,000 emails a day, this represented an enormous and costly manual labor bottleneck at the very front of the shipment lifecycle.
C.H. Robinson's GenAI engineering team built an AI agent system using LangChain's open-source framework as the foundation. LangChain's model-agnostic design was specifically valued — it allowed the team to swap underlying LLMs without rewriting application logic, preserving optionality as the model market evolved rapidly. For the more complex classification tasks that required tracking decision state across multiple steps (particularly load type determination), the team adopted LangGraph. LangGraph's structured state management and debugging capabilities through LangGraph Studio allowed engineers to inspect and correct agent behavior during development without the unpredictability typical of early agentic systems.
LangSmith provided real-time observability across the entire fleet of running agents. Subject matter experts used it to identify failure modes before deployment and to quantify application performance at scale through trace analysis. The team also used LangSmith's prompt management tools to experiment with and measure different prompting strategies against the same baseline datasets, building systematic confidence in the system before expanding capacity.
The production results are concrete. Approximately 5,500 orders are now processed automatically every day — end-to-end, from email ingestion through order creation and tracking initiation. The shift saves more than 600 hours of manual email handling per day across the operation. C.H. Robinson is now extending the platform's scope, building toward deeper personalization and fuller automation of the logistics lifecycle, including exception handling and carrier communication.