From weighing scale to visual recognitionFrom weighing scale to visual recognition

The R&D effort produced Detect, launched in early 2025. It is a self-service scale with built-in automatic image recognition: the shopper places the product on the tray, the camera captures the image, and the algorithm identifies it, calculates the price and prints the label. The process is instant and requires no assistance.

The system was designed with a strong focus on usability: the interface is clear, the flow is intuitive and people of any age can use it without difficulty. It is sold mainly to supermarkets and wholesalers for their produce sections, and the model has already been adapted to recognize cheeses and cold cuts as well.

In parallel, the R&D team began bringing AI tools into its own internal processes: coding assistance, software development and automated quality-control testing. AI first entered the product and from there spread across the team's entire operation.

The most immediate impact was financial. The recognition system's accuracy directly reduces product identification errors at the point of sale: cheeses or cold cuts weighed at the wrong price mean real losses for the retailer. In high-volume operations with many similar products, the difference shows quickly.

In one case documented by the team, the owner of several wholesale stores recouped the cost of the equipment in the second month of operation, thanks to fewer errors when selling variable-price products.

Beyond the product, Systel now has a team that knows how to build, train and scale image recognition models, with its own platform for updating those models from anywhere in its network of installed equipment. That technology asset opens the door to new applications in segments the team is still exploring.

The company trained all its teams in using AI tools, with one core message: the technology is here to make work more productive, not to replace people. It's the same approach the company took when it introduced Office or email.

The response was positive. Most staff already used some AI-powered tool in their daily lives, which made adoption easier. At the same time, IT security policies were put in place to protect corporate knowledge. Leadership actively drives this culture: the CEO takes part, managers encourage everyday use and the R&D team shares experiences with other departments through internal talks.