Manual quality control processes in manufacturing are often slow, inconsistent, and prone to human error, leading to increased defect rates and reduced operational efficiency. Traditional visual inspection methods lack repeatability and struggle to adapt to variations in product appearance or complex geometries.

Scortex offers an AI-powered visual inspection solution, Spark, that automates quality control by leveraging deep learning algorithms. Spark provides real-time monitoring and analysis of product quality, significantly increasing inspection speed and accuracy compared to manual methods. The system uses a camera or multi-camera setup with adjustable arms to capture images of parts, and requires as few as 30 conforming parts to train an AI model specific to the product. Spark's software platform offers an intuitive interface, local algorithm processing, and a touch screen for easy operation. The Quality Center module allows users to monitor and analyze quality in real-time, perform root cause analysis, and generate detailed reports accessible via the web.

Automated visual inspection using deep learning algorithms

Spark and Spark Multi View (2-4 cameras) hardware options with adjustable camera positioning

Rapid deployment requiring only 30 conforming parts for AI model training

Inspection speeds up to 3 parts per second

Embedded algorithms for local processing

Touchscreen interface and central processing unit

Quality Center module for real-time monitoring, root cause analysis, and report generation

ROI calculator to estimate return on investment

Scortex targets manufacturing companies across various industries, including automotive, cosmetics, and industrial goods, seeking to automate and improve their quality control processes.

Scortex provides a ROI calculator to estimate the return on investment for potential customers. Based on the calculator, some customers see an estimated amortization in 4 months.