C.H. Robinson has launched a new AI system for its 4PL Managed Solutions customers. The software is designed to run a shipper's global supply chain while assessing and improving performance.
The product, called Lean AI Engineer, works alongside Lean AI Planner, which C.H. Robinson introduced earlier, to form what it describes as a closed-loop system. Lean AI Planner manages shipments in real time, while Lean AI Engineer reviews operations, identifies patterns and recommends changes that can influence future decisions.
The system can assess an entire supply chain in 25 to 30 minutes, compared with more traditional reviews that can take up to four weeks and are often based on past performance rather than current conditions, according to C.H. Robinson.
The technology is already autonomously handling 92% of 4PL shipments globally across trucking, ocean, air and rail, the company said. That includes processes from order creation through tendering, routing, delivery, exceptions and carrier payment.
Jordan Kass, President of Managed Solutions at C.H. Robinson, said the significance of the system lies in the link between execution and analysis.
"The breakthrough here is that it's one closed-loop AI system," Kass said. "It will run continuously, improve the operation it's running and heal itself when something breaks - without an alert or a human noticing a problem first. The Lean AI Planner executes in real time while the Lean AI Engineer studies the results, identifies patterns, adapts logic and influences future decisions. Just like we launched Managed Solutions to break down the barriers between TMS, 3PL and 4PL services, this technology ends the need for separate supply chain intelligence and orchestration tools. It's what businesses with complex logistics have wanted for decades."
C.H. Robinson's 4PL business manages logistics on behalf of customers that use multiple carriers, transport modes and routing options. In that environment, the company is positioning the new AI system as a way to reduce reliance on manual intervention in day-to-day transport management.
Kass said that work has traditionally depended on experienced staff making decisions and responding to disruption.
"This level of premium logistics service has traditionally depended on talented people to manage complexity, make smart decisions day to day and intervene during disruption," Kass said. "The problem was that talent didn't scale. We've changed that by encoding expertise in the technology itself. Shippers will get infinite talent and expertise, consistently applied across every shipment, regardless of who's available in what time zone or how much their shipping volume grows or spikes. Their team and our team can focus on strategic priorities and driving the best business results."
The AI models rely on a proprietary context layer built by C.H. Robinson's in-house software engineers and data scientists, according to the company. That layer draws on institutional knowledge from workflows and freight specialists, alongside operational shipping data gathered from customer supply chains.
C.H. Robinson said the system analyses factors such as goods, procedures, pickup and delivery locations, carrier choices, routing preferences and risk tolerance. The goal is to generate recommendations that reflect each customer's operating conditions rather than broad benchmarks.
"Our technology truly understands your supply chain from the inside out, because the AI leverages all the data on all the steps of your shipping end to end, not just the parts of your supply chain that disparate tools see," Kass said. "It also has the benefit of being trained on the unique context we have from orchestrating your freight - the large and small details about your goods, your procedures, each pickup and delivery location, your carriers, your routing and risk tolerance. That's how the Lean AI Engineer knows which improvements are right for you, instead of making generic or theoretical recommendations. If you're an auto-parts maker shipping cross-border to a just-in-time assembly line five days a week, it won't suggest how much you could save by shipping once a week."
The first release of Lean AI Engineer focuses on identifying operational changes and hidden savings, C.H. Robinson said. It cited one early user that reduced loads by 17% across 20 locations by moving from a varied shipping schedule to once-weekly shipments, with annual savings of more than USD $1 million.
Another customer was advised to reorganise shipments so that one pickup served three delivery locations. According to C.H. Robinson, that change would reduce loads by 81% and cut costs by 40%.
Wider use
C.H. Robinson said the system will be made available to more customers and expand its analysis into additional areas such as carrier performance. The software will monitor carrier behaviour across lanes, transport modes and customer accounts to identify signs of declining service and recommend corrective action, according to the company.
Arun Rajan, Chief Strategy and Innovation Officer at C.H. Robinson, said the main issue in supply chains is often the gap between identifying problems and acting on them.
"Supply chains do not generally suffer from a lack of information. They suffer from the gap between knowing and doing," Rajan said. "Tech that sits above or outside of a supply chain can aggregate data, harmonize signals and recommend. But it relies on someone else to execute on the signals and someone else to learn whether those actions worked. Our tech closes the gap, delivering 24/7 premium service with one unified system no one else can match."
C.H. Robinson said it manages 37 million shipments a year, representing USD $23 billion in freight, and works with 75,000 customers and 450,000 carriers.