Deciphering messy emails and handwritten PDFs took employees 7 minutes per order. Now, AI parses the unstructured data to build orders.
One of the world's largest global logistics providers manages 37 million shipments a year by ocean, air, rail, and truck for 83,000 customers.
The company receives 15,000 shipping request emails daily, often containing inconsistent formatting and handwritten notes on PDFs. Employees spent up...
Third-party logistics and supply chain management services provider.
Framework and developer platform for building LLM-powered applications.
C.H. Robinson's Order processing is part of this use case:
Related implementations across industries and use cases
Manual processes bottlenecked 34 ports and 270 vessels. Now, employees deploy AI agents to balance containers and optimize fleet speeds.
Rate limits capped geocoding at 2,000 requests/min. A fine-tuned LLM now clears 8,000/min—cutting costs by 80%.
Staff manually searched files to resolve vessel delays. Now, they use Copilot to organize past data into tables for rapid responses.
Manual checks of varied supplier documents bottlenecked financial close. Now, AI matches contracts, routing discrepancies to specialists.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.
Complex logistics terms bottlenecked output. AI trained on definitions now drafts posts, helping new hires ramp in three weeks.
Tracking freight required manual portal searches. Now, an AI assistant instantly retrieves real-time shipment data across backend systems.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.
Deciphering messy emails and handwritten PDFs took employees 7 minutes per order. Now, AI parses the unstructured data to build orders.
One of the world's largest global logistics providers manages 37 million shipments a year by ocean, air, rail, and truck for 83,000 customers.
The company receives 15,000 shipping request emails daily, often containing inconsistent formatting and handwritten notes on PDFs. Employees spent up...
Third-party logistics and supply chain management services provider.
Framework and developer platform for building LLM-powered applications.
C.H. Robinson's Order processing is part of this use case:
Related implementations across industries and use cases
Manual processes bottlenecked 34 ports and 270 vessels. Now, employees deploy AI agents to balance containers and optimize fleet speeds.
Rate limits capped geocoding at 2,000 requests/min. A fine-tuned LLM now clears 8,000/min—cutting costs by 80%.
Staff manually searched files to resolve vessel delays. Now, they use Copilot to organize past data into tables for rapid responses.
Manual checks of varied supplier documents bottlenecked financial close. Now, AI matches contracts, routing discrepancies to specialists.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.
Complex logistics terms bottlenecked output. AI trained on definitions now drafts posts, helping new hires ramp in three weeks.
Tracking freight required manual portal searches. Now, an AI assistant instantly retrieves real-time shipment data across backend systems.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.