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Optimizing Shipping Costs for a US Retailer with a Computer Vision-based Box Measurement Solution

Our client is a popular women’s fashion retailer with over 550 locations in the US and Canada, as well as scaling e-commerce operations. They sought to optimize the expenses incurred in packing and shipping products ordered online. 

KamerAI helped them achieve this — with KamerAI’s computer vision-based packaging measurement solution they saved over 10% in logistics expenses.

The challenge

Our client shipped their products through a leading logistics company. The facility processed on average 4,000-5,000 items a day, which rose to 8,000-10,000 during peak seasons. However, they did not have a mechanism to record these details before they left the warehouse. The shipping charges were decided by the logistics partner based on the dimensions or weight, whichever was greater. 

Without clear visibility into the way in which the price was determined, our client had no way to optimize costs.

KamerAI’s approach

The box measurement solution, our managed services offering, helped the client gain granular visibility.

We worked with the client to install a KamerAI appliance, two cameras over a conveyor belt, and a UI for easy use. This system collected the data and stored it in KamerAI’s database. We’d got the system up and running within a week, and it began collecting data immediately. 

It scanned each package as it was being prepared for shipping. The cameras took two images of each product: a close up and a long shot for visual records. It captured the barcode (which the AI decoded), address and tracking details. It also recorded the dimensions such as length, width and height of the packages. In the first month, the solution processed around 200,000 packages at a single warehouse.


Based on the images, we identified the following opportunities for cost-optimization.

Box sizing: Products were not always packed in boxes that were the right size for them. Sometimes, even small products incurred high delivery costs when they were packed in large boxes.

Disputes and auditing: Whenever our client disagreed with the logistics provider’s pricing, they raised corrections. While this sometimes reduced the shipping costs, it added an audit fee to the bill. 

In addition to setting up a scientific trail of package dimensions and weight, we also used the extensive data we collected to help the logistics partner identify inaccuracies in their system.

KamerAI’s long-term solution

With clear visibility into the gap, we built a new feature that would automatically compare KamerAI’s dimensions with those of the logistics partner. It automatically identified major differences, attached the images and published them in a deviations report for the client.


Our client saved nearly 10% in logistics expenses from using KamerAI’s box measurement solution.

  • Analytics data enabled the client to choose the right cartons for every product.
  • Automated visual data capture saved time and resources spent in manual inspections. 
  • Audit fees reduced as the client had detailed deviation reports.
  • This also put them at a better negotiating position for future deals.

Future outlook

Working closely with this client, we understand that this is a common inefficiency in the logistics landscape. Computer vision-based analytics technology empowers manufacturers, retailers and logistics players with the visibility they need to optimise efficiencies. 

If you would like to identify opportunities for cost savings in your packaging and shipping, speak to a KamerAI consultant today.