For whom

Manufacturing companies, security companies, retailers.

Technologies used

Computer Vision, AI/ML, YOLO, OpenCV, TensorFlow, PyTorch, Convolutional Neural Networks (CNN).

Challenges

Low product quality, high quality control costs, facility security.

Example

Product quality control on a production line

Problem Description: A manufacturing company approached us with a request to improve product quality control because the existing control methods were not efficient enough and required significant manual labor.

Solution: We analyzed the current processes and developed a computer vision system based on OpenCV and YOLO, integrated with the production line. The system uses high-resolution cameras to capture product images and neural networks to identify defects.

Result: Implementation took four months. As a result, the company reduced defects by 35%, reduced quality control costs by 20%, and increased overall productivity by 15%.

Safety Monitoring in a Warehouse

Problem Description: A large retailer approached us with a request to improve security in a warehouse that was experiencing frequent theft and damage to goods.

Solution: We implemented a computer vision-based monitoring system utilizing TensorFlow and PyTorch technologies. The system includes cameras installed throughout the warehouse that analyze the movement and actions of people. In case of suspicious activity, the system automatically sends notifications to the guards.

Result: The implementation took 3 months. As a result, theft incidents were reduced by 40% and security efficiency increased by 25%.

Automatic recognition and sorting of goods

Problem Description: A manufacturing company approached us with a request to automate the sorting of goods in the warehouse to reduce processing time and minimize errors.

Solution: We designed and implemented a Convolutional Neural Networks (CNN) based system for automatic product recognition and sorting. The system uses cameras and robots to identify and move goods to the appropriate storage areas.

Result: Implementation took five months. As a result, the company reduced sorting time by 50