Maddox Keyvisual

AI-Based Visual
Quality Control

With Maddox AI, you can reliably automate and digitise your quality control by simply annotating a few defect images - without any investment risk!

About our solution
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Maddox Keyvisual
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Maddox Keyvisual
Leading industrial companies rely on Maddox AI:
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Benefits

Maddox AI: Your Benefits at a Glance

Maddox AI offers you numerous benefits over traditional quality control systems. Our cost-efficient solution can inspect even the most complex components, reducing recalibration efforts and pseudo-rejects. You can train, evaluate and optimise AI models for your quality control independently, without the need for deep AI knowledge. By processing the relevant production KPIs, our cloud software also provides valuable insights into production quality. And best of all, we take on the complete investment risk for each new inspection system!
0 x
recalibration
> 0 %
less pseudo scrap
0 %
risk free
0
AI-Expertise necessary
0 %
digitized analyses
Affiliated with
Uni TübingenMax Planck InstitutGeorg August Uni Göttingen
An official
maddox
Startup

Free White Paper: Why Aren't More Companies Using AI-Based Visual Inspection Systems?

Find out in our white paper why only a few companies are using AI systems in regular operation, although the majority is convinced of the great added value of the systems. Read now!
software-solution

Our Cloud Software at a Glance

Our cloud application allows you to create customised AI models without the need for AI expertise. The intuitive cloud software simplifies the model development process and ensures that you automate and digitise your inspection tasks quickly and efficiently.
Maddox Video Frame
  • Easy creation and maintenance of digital fault catalogues

  • Intuitive annotation of errors to be detected automatically

  • Transparent feedback on whether data quality is sufficient to train AI models

  • Train AI models with a few clicks

  • Reliable updating of models in your production lines

  • Easy creation and maintenance of digital fault catalogues

  • Intuitive annotation of errors to be detected automatically

  • Transparent feedback on whether data quality is sufficient to train AI models

  • Train AI models with a few clicks

  • Reliable updating of models in your production lines

Hardware-solution

Powerful Hardware Solutions for Individual Inspection Tasks

With the help of our flexible hardware components, a wide variety of applications can be reliably automated. Whether it is the inspection of components in the automotive industry, the quality control of injection-moulded parts in the plastics industry or the inspection of smallest elements in electronics production - we adapt our hardware precisely to your application to ensure precise and efficient quality control. If required, we can of course also reuse hardware that you have already installed. If you already have high-performance camera systems that basically produce sharp images but struggle with too high pseudo scrap, we can also optimise your existing camera systems with our solution and reduce your pseudo scrap.
case studies

Many Inspection Tasks Can Be Automated With Maddox AI

Explore our case studies to find out how Maddox AI optimises quality control in industries such as automotive, plastics, electronics manufacturing and many more. Read about the individual challenges our customers have faced and how they benefit from our customised solutions. Use our filter options to search specifically by industry, application area or material properties and find relevant case studies.
Industry

Industry Overview: Diverse Applications in Quality Control

Maddox AI is already performing visual inspection tasks in a variety of industries. Our software is versatile and enables visual inspection of products in a wide range of application areas. Our team of experts will be happy to explain whether our solution can also automate your visual inspections.
FAQ

You Have Questions? We Have Answers:

Here you can find a collection of the most frequently asked questions on the topics of AI-based visual quality control as well as automation and digitalisation of inspection tasks. If you have any further questions, our team of experts will be happy to help!
What is the difference between classic and ML-based visual quality control?
Classic systems are given rules to recognise defects. A ML model, on the other hand, learns from examples whether a part is OK or NOK. In this learning process, the model derives implicit rules that do not require explicit programming (e.g. "NOK, if scratch on top left"). Machine Learning allows Maddox AI to automate even very complex use cases, such as surface recognition.
As a user, can I use Maddox AI without a technical or artificial intelligence background?
Yes, Maddox AI's software is designed in such a way that everybody can train AI models and put them into use after an initial thirty-minute training session.
How much does Maddox AI cost?
This depends on the specific use case. Before we start with a Maddox AI project, we show you transparently how much the use of Maddox AI would cost. Based on this, you can calculate your business case.
Can Maddox AI reliably inspect even at very high production speeds (e.g. several parts per second)?
In the vast majority of cases, high production speed is not a problem. Our models run on our industrial PC at your site, which means that the AI model analyses images within milliseconds. In our experience, it is the part handling rather than the AI evaluation that becomes the possible automation bottleneck.
How long does the implementation process of the Maddox AI system take?
This depends very much on how quickly we get enough data (pictures of OK/NOK parts). Since Maddox AI is an AI system, data is very important as a basis. We therefore always ask our customers to collect bad parts in advance. We can usually record these parts directly on the installation day and ideally already have enough data to train the model. In this case, the implementation only takes a few days. If we need to collect more data, the system can also run for a few weeks before the implementation is completed.
How much data (=annotated images) does Maddox AI need?
The important thing is not necessarily the amount of data, but its diversity. This means that different appearances of error types are relevant for a good and representative sample of defecets. We do not need many OK images, as the diversity in these images is usually smaller than for NOK images. Accordingly, our focus is on images with defects. We can give you the following rough rule of thumb: In 90% of the cases, 50 images per task (e.g. 50 NOK images of a defect class) are sufficient. In 10% of the cases, another 50 images (i.e. 100 in total) are needed to reliably adapt the Maddox AI system to your use case.
Can Maddox AI integrate with my software systems (MES, PLC, Data-Lake, etc.)?
Yes, this is not a problem. Maddox AI makes the results of the AI available via several protocols that are common in the industry, such as OPC-UA, REST API, MQTT, Modbus TCP or simple digital I/O.
Does Maddox AI make sure that there are no people visable in the images it takes?
Yes, Maddox AI places great emphasis on this. The Maddox AI system provides the ability to recognise people in the images to blur or black them out before uploading them to the cloud. No one has access to the people's identities - not even we can recover these images.
Will I receive new software updates regularly over time?
Yes, Maddox AI is a classic SaaS (software as service) solution. Accordingly, you will receive software updates regularly and free of charge.
Do I have to pay separately for software updates, maintenance and other after-sales services?
No, the software updates, maintenance and other after-sales services are included in the licence fee.