EyeC ProofRunner Empowered by AI

We Unite Efficiency, Sustainability and Quality.

Isolate irrelevant suspicious areas such as dust and material inclusions
and reduce your waste.

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Our solution for today

With our new AI Image classification, detected deviations can be filtered by typical and relatable classes.
Benefit from our pretrained neural Networks today to increase the performance and efficiency from the first day.

Efficiency​

Increase your overall equipment efficiency (OEE) by focusing on relevants defects only.

Quality

Make no compromises in quality and find smallest defects that are crucial to you.

Sustainability

Achieve maximum inspection performance no matter the substrate. Even recycles!

Efficiency​

Reduce waste and increase your overall output.

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Ask the Experts:

In the first episode, EyeC Inline Inspection expert Tim Wedemeier takes a closer look at how EyeC is using artificial intelligence to transform print inspection and revolutionize quality control.

In the this episode, EyeC Inline Inspection expert Benedikt Fiedler dives into the critical role of AI training in print inspection. You’ll learn why high-quality, expertly sorted defect data is essential for accuracy.

In the this episode, we answers a key question: Do you need special hardware, or can your existing EyeC system run the AI-based defect classification?

In this episode, we answer a key question: What Defect Classes are Available?

In this episode, we discover how EyeC’s AI-driven defect classification helps streamline your workflow by prioritizing only the most relevant deviations – helping you concentrate fully on maintaining high print image quality and ensuring smooth production.

How can print inspection’s Overall Equipment Effectiveness (OEE) be enhanced by artificial intelligence (AI)? In this episode of Ask the Experts, Benedikt explains how AI-driven defect classification lowers waste and rework, boosts productivity, reduces downtime, and improves quality assurance for flawless prints.