Revolution on the Used Device Market: How Automation is Leading the Way

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The main trend in the used device market is automation. All processes that are done manually have one common drawback: human errors.

People make mistakes, and only automation can avoid them. So, let's discuss how processes of used device businesses can be optimized by implementing automated solutions.


Manual device testing is an outdated approach. It is incredibly time-consuming, requires employee training and largely depends on how responsible the worker is. Moreover, this method leaves space for fraud by customers or even employees. Therefore, manual testing shouldn't be used, especially in wholesale mobile phones businesses.

Instead, try software testing like NSYS Diagnostics. This solution provides 60+ tests to detect over 100 hardware defects and completely eliminates human errors.


While automated functional tests have been on the market for a long time, automating a subjective process like the cosmetic condition check was challenging. However, NSYS Autograding has solved this problem! With an automatic grading system, this AI-powered solution quickly evaluates the device. What else does NSYS Autograding provide?

  • Customizable scoring system;
  • No hardware required;
  • Simple implementation and in-app tutorial;
  • Consistent assessment across diverse devices.


Data wiping can be performed simultaneously to speed up the process. This automation will save you time and make the process more predictable. With NSYS Data Erasure, up to 60 devices can be connected to one computer at once. For each device, you will get a certificate that confirms that data was deleted in compliance with international standards.

Automated Ecosystem

The most advanced option is to automate all interconnected processes. This will drastically increase the workflow's efficiency and help you get deeper insights from the analytics. 

Try NSYS All-in-One, which connects all services needed for the used device businesses. It offers automated diagnostics, data erasure.

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