How Agaris automated CMRs with 99.8% accuracy
For Agaris, CMR transport documents contain information, like the number of pallets at loading and unloading, with direct operational value. Extracting that information manually from every CMR was unnecessarily expensive to capture at scale.
99.8%
accuracy
86%
fully automated
Challenge
CMRs vary in layout and can arrive mixed with other logistics documents. Teams had to first identify the correct document and then find the relevant pallet quantities, turning a repetitive lookup task into a recurring operational workload.
Approach
Skwiz automatically identifies the CMRs, reads the required pallet information and applies validation rules before the data moves on. Documents that cannot be approved automatically are routed to a validation interface for human review.
Lanark, Skwiz's logistics and supply-chain partner, managed the project and translated the operational requirement into a focused automation flow. The model was set up to perform across CMR variations and uses clear approval thresholds so high-confidence documents can pass without human intervention.
Result
The live workflow reaches a 99.8% accuracy rate and fully automates around 86% of the documents. Remaining cases stay under human control.