AI video analytics for quality and production control

Detect errors in real time.

Keep an eye on your production quality

AI video analytics for quality and production control offers you an intelligent solution to visually monitor manufacturing processes and detect deviations early. In modern production lines, every irregularity counts—because even the smallest errors can cause scrap, production delays, or complaints. If an error is not detected immediately, entire batches of faulty products often result. This leads to rework, material waste, recalls, or in the worst case, loss of reputation and customer trust.

When Classical Systems Fail: Why Your Production Overlooks Errors

Classical systems operate according to fixed rules: “If the distance between point A and B is less than 2 mm, then it is an error.” These rules must be manually defined by a human, so the system only knows what it has been explicitly taught. The system does not “understand” what a good or bad part is. It only compares individual features with predefined tolerances. These algorithm-based systems are reliable in clearly defined tasks, such as dimensional checks, position recognition, or reading coded characters (e.g., barcodes). However, classical methods encounter limitations in complex or variable scenarios: If an error occurs that is not covered by these defined features, the system does not recognize it

Say goodbye to overlooked errors – rely on visual AI inspection

AI-based video analysis takes a fundamentally different approach. A key feature of AI-supported systems is the ability for visual anomaly detection: Through model training, these systems first learn the normal (the desired condition of defect-free parts) and then detect deviations from it. This allows novel or previously unknown error patterns to be identified without being explicitly programmed in advance. The AI “understands,” in a way, what a flawless product looks like and signals anything unusual as a potential defect

AI video analytics can achieve higher product quality, lower costs, and greater process efficiency in quality control.

Our Vaidio technology precisely controls production quantities and quality. The AI is specifically trained using specific material and product images to reliably detect defective products. Through this process, the AI identifies company-specific deviations such as shape or surface defects at an early stage, reduces the number of defective products, and continuously optimizes the efficiency and quality of production processes. In general, industries with high quality requirements, extensive inspection scope, or costly error consequences particularly benefit from AI-powered video analytics.

Industrial manufacturing and electronics

AI video analytics inspects, for example, surfaces of components for scratches, cracks, dents, or material defects in real time. It detects paint defects on body parts, soldering defects on circuit boards, or assembly errors in final device assemblies.

Automotive industry

The automotive industry, with its high quality standards (keyword “zero-defect target”), is a pioneer in the use of AI in quality control. Body parts, electronic modules, or engine components are fully automatically inspected for defects such as hairline cracks, dimensional deviations, or assembly errors. The AI detects critical flaws that could affect vehicle performance or safety (e.g., crack formations, misdrilling, incorrect gap measurements) and thus ensures seamless quality control of every component.

Steel and metal industry

Here too, AI video analytics can be used to detect surface defects on rolled steel or sheets (e.g., scratches, inclusions).

Pharmaceutical industry and medical technology

In regulated industries like pharma and medtech, quality is of utmost importance because errors can directly pose safety risks to patients. AI-based video systems are used, for example, in packaging and label inspection of medications. Algorithms compare printed batch information, barcodes, or leaflets with the target data and detect deviations such as incorrect or incomplete printing, mix-ups, or damaged packages in real time. Compared to manual sampling, this has drastically increased inspection speed and nearly eliminated error rates, ensuring cost savings as well as compliance with strict regulatory requirements. AI video analytics can also be used to inspect injection vials for particles, check tablets for visual defects (breakage, discoloration), or inspect surgical instruments for surface defects.

Food and beverage industry

AI-powered quality control is also gaining importance in the food and beverage sector. Here, alongside product quality, food safety is a major focus. AI video analytics can be used on production lines to detect foreign objects. Besides foreign objects, the AI can also monitor quality parameters such as the shape and color of food items (e.g., browning level of baked goods, fill level of bottles, sealing of packages). Misfilled or damaged packages are detected and removed without employees needing to inspect each item individually. The result is less scrap, optimized sorting processes, and increased overall efficiency.

Solar industry (photovoltaics)

With AI video analytics, solar panels are inspected during production for microcracks or cell defects — an AI can detect cell fractures within seconds that are barely visible to the human eye, allowing early sorting of defective modules. A pilot project in solar cell manufacturing showed that, besides significant time savings, the error detection rate improved with AI inspection, as the system consistently identified tiny cracks over hours while human inspectors lost concentration as their shifts progressed.

Vaidio Data – Intelligent process optimization with AI and LLM support

Target bottlenecks, inefficient processes, and recurring sources of error: When and where do errors occur? Which machines are particularly prone to failures? At which process steps do quality issues arise? Vaidio Data provides you with well-founded answers — automatically, contextually, and clearly explained.

Clear evaluations instead of raw data chaos

Thanks to Vaidio Data and the LLM component, you receive clear visual analyses and documentation in natural language. This saves time and makes complex data immediately actionable.

Prevention instead of reaction

By knowing when, where, and why errors occur, you can prevent future disruptions before they happen—and actively optimize your maintenance and production.