Using machine vision technology to streamline an e-commerce experience


How can improve the efficiency of a e-commerce business reliant on specialized parts replacement?

The Challenge

Green Masters e-commerce business is driven by existing customers looking for replacement parts and components to maintain their existing equipment.

Identification of the correct replacement parts was forming a bottle neck in the process and often resulted in missidentified items. The existing process was a very time consuming and manual one invlolving discussion with the customer, browsing through thick spare part catalogues, and always carrying the risk of ordering a wrong component. We automated this entire process with machine vision technology and integrated the identification process directly into a new e-commerce platform.

Our Contribution



  • Product Strategy
  • Product Roadmapping
  • User Research & Testing


  • Service Design
  • UX Design


  • Technical Architecture Planning
  • Machine Vision (BigTransfer)
  • AI engineering & Machine Learning
  • Cloud Services technologies (AWS)
  • API Development

Machine vision identification

Through a WhatsApp integrated service, you can quickly and easily take a photo of the broken component and send it directly to Green Master. Once in our system, our machine vision application uses identifiable data points from the submitted imagery to match it to an item in the Green Master catalog of parts with a far higher degree of confidence than the manual process.

Direct link into E-comm ordering

Once an item is identified the system will automatically reply with a link to the identified part within the Green Master e-commerce platform, where you a user can directly purchase their replacement or new component in confidence that their order will match their need.

Streamlined results for all users

The efficiencies created by the system impacted not just Green Master as a company, but also their customers. The reduction of manual consultation and resolving ordering issues meant vast time savings at Green Master. The reduction in miss-identified parts meant more satisfaction for their customers who’s confidence in the product, and Green Master, greatly improved as a result.

Project Highlights

  • Created a far faster and more fluent buying process for Green Master’s online customers

  • Machine vision solution to facilitate and ease Data Collection and parts identification
  • Streamlined process created a vast amount of time and effort savings for Green Master

  • Decreased the chance for error in the parts identification and checkout phases of purchase

Key Technologies Used


Juha-Matti Tirilä

Data Scientist, Programmer •  Oulu
We developed this with some of the newest technical solutions available, so this was a very exciting project for us. I think this demonstrates how quickly we can adapt to new technologies and create the best value possible for the customer.

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