Artificial Intelligence (AI): Field-proven applications for companies

Our goal: Guarantee permanent data sovereignty, data protection and traceable results for your company in application-oriented AI solutions.

For increasing numbers of companies, artificial intelligence is becoming a crucially important approach for optimizing workflows, increasing productivity and securing competitive advantages. For the most part, AI helps them with applications where traditional solutions are not efficient enough or come up against their limits. And although not every task can or should be solved with AI, in the case of well systematized and documented projects with a very good historical database to draw on, using AI definitely makes sense.

In principle, any company can use artificial intelligence, as the AI offers currently on the market range all the way from cheap off-the-shelf solutions to expensive customized ones. One thing that these offers and technologies generally have in common is that they require the use of cloud servers, which are usually situated outside of Europe. If you want to use AI without external clouds, however, special AI hardware or an AI-on-the-edge solution are alternatives. Moreover, standard solutions are also unsuitable for solving challenging tasks, such as ones that require low latency or particularly high energy efficiency.

This is where our offer comes in. We help our customers and partners master their challenges in a practical, customized manner using various artificial intelligence approaches. Our solutions are tailored particularly to use cases in which permanent data sovereignty, data protection and high processing speed are vitally important, as well as the traceability of the processes by which the AI systems arrive at their results.

Our intelligent systems expertise

We see artificial intelligence as part of a comprehensive toolbox with which we can solve the challenges of our customers and partners in a highly optimized fashion according to the specific task at hand. In relation to AI, we pursue various technological approaches – from pure data analysis with algorithms, to private cloud and edge solutions, to the implementation of projects using high-performance AI computing hardware (embedded systems). In this way, we retain lots of flexibility to achieve optimally reliable and efficient customized solutions, including for small and medium-sized enterprises.


Whether foundational training courses that give you a sound basis for understanding AI concepts, or intensive training courses that allow you to address the needs of your company in a deeper and more targeted manner: with our know-how and that of our cooperation partners, you will attain the ideal mindset to implement AI with structure and focus in successful use cases.

Near-sensor data processing

To support high processing speed and data reduction, we employ a near-sensor approach in data processing. This involves analyzing, evaluating and classifying readings in the sensor, so that subsequently only the data required for the evaluation and training of AI systems has to be forwarded.


When teaching an AI system, we always include expert knowledge about the respective use case, so that systems are trained more quickly and above all more reliably. The objective of our work in all cases is for the systems to fulfill high requirements with regard to robustness and reliability, which we are able to guarantee by virtue of our longstanding expertise in domains such as system verification and functional safety.

Analysis software / algorithms

In practice, there is often a lot of data available, but it is not always the right data for solving a problem. That being so, we use model-based approaches such as digital twins or simulations. This enables us to model all the necessary manifestations of a problem without the need for the laborious teaching of AI systems in real environments. With this approach, we also take AI out of the black box and make it possible to retrace the paths along which our systems arrive at solutions with the help of methods such as machine learning and big data analyses.

Analysis hardware

When it comes to using AI without external clouds, special AI hardware that performs the data processing internally can be the method of choice. We are able to implement hardware solutions with great efficiency through our modular hardware configuration (all the way down to chiplets), state-of-the-art packaging methods, rapid generation of building blocks and, upon request, the integration of our AI algorithms. Altogether, this creates particularly resource-conserving and data-reduced solutions that are not only small, but also involve minimal energy consumption.

AI infrastructure

If a company wants to avoid data storage in external clouds, we can help it get set up with local computing infrastructure using private cloud or edge solutions. In addition, 5G technologies can be an effective approach for applications that use smart connectivity or require the rapid transport of large data volumes. 5G’s ultra-short latency times combined with extremely low energy consumption allow applications such as real-time sensor systems or new forms of process control and configuration.

Our AI know-how at a glance

AI offers EAS

Our AI-Trainings

E-Learning: AI Essentials (on-demand)

Our basic training course offers the ideal foundation for company employees who are new to the world of artificial intelligence (AI) and machine learning.

In a one-day online training, which you can access on-demand at any time, we offer you an introduction to content and methods and create a basic understanding of AI. The learning content ranges from basic explanations to best practice examples and use cases to demystifying the technologies behind AI-based solutions.


Key seminar topics


Develop a general understanding of the subject of artificial intelligence, its value drivers, and the performance of AI solutions in economic applications.

Join the discussion:

Acquire knowledge of relevant terminology, concepts, and technologies in order to understand the feasibility and progress of AI projects at your company.

Develop skills for evaluating decisions:

Get a basic feel for the evaluation of decisions around when it is sensible and feasible to use AI at your company and when it is not. Take methodological knowledge with you to introduce and set up an AI project.

Intensive Training for Professionals and Executives

The intensive training course “Chief Data-Driven Business Manager”, which we provide in collaboration with the INC Innovation Center, provides participants with a proven methodological approach from idea generation and feasibility to data testing and agile implementation methods for AI.

After this five-day training, professionals and executives will be able to apply the field-tested methods of the AI Navigator and data-driven business model canvas in order to identify and evaluate economically logical AI use cases.


Key seminar topics


Learn about agile development methods and how to ensure the quality of your solution.


Apply the AI Navigator and the data-driven Business Model Canvas in your own company in order to successfully identify and evaluate potential AI use cases.


Focus specifically on the user experience when implementing your AI solutions and take the impact of AI on digital business models into account.

Examples of AI projects at Fraunhofer IIS/EAS

  • Universal sensor platform (USeP)
    Universal sensor platform (USeP)
    • Universal sensor platform for IoT and AI systems
    • Suitable for systems with high demand for local signal and computing power combined with low power consumption (edge computing)
    • Combination of state-of-the-art configuration and packaging technologies with cutting-edge semiconductor design methods
    • Permits the integration of various sensors
  • Industrielle Datenanalyse
    © hramovnick /
    • Increasing efficiency in production and optimizing processes through the use of AI algorithms
    • Condition monitoring of machines and systems
    • Predicting wear and corresponding needs-based maintenance

    Read more about AI in production

  • Automated car production line
    © artstudio_pro - Fotolia
    • Reliable monitoring and early detection of faults in wireless communication
    • Using machine learning methods to evaluate and permanently assess the condition of wireless traffic
    • Rapid detection of connectivity problems and their causes
  • Simikom
    © Leistungszentrum mikro/nano
    • Structurally integrated intelligent sensor/actuator technologies
    • Monitoring and adaptive control of machine tools and production processes

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Consortium Project »AI: understand – apply – benefit«

We are joining forces with KEX Knowledge Exchange AG to support companies in developing their AI know-how. The goal is to enable the project partners to take their individually optimal path to using AI profitably, and to secure competitive advantages.


Industrial data analysis at Fraunhofer IIS/EAS

The increasing digitalization and networking of production processes in the context of Industry 4.0 is leading to numerous challenges that demand innovative solutions. A particular focus lies here on the automatic data analysis of measurement and process data for intelligent condition monitoring and quality assurance.


AI basic training

Our basic training courses offer the ideal foundation for company employees who are new to the world of artificial intelligence (AI) and machine learning. In a one-day (online) training course, we provide you with an introduction to the content and methodology as well as a basic understanding of AI. The course content includes everything from basic explanations to examples of best practice and use cases, as well as a demystification of the technologies behind AI-based solutions.

AI in Saxony



Artificial Intelligence – Expertise and Innovation Potential in Saxony

AI maps Saxony

See at a glance which players in research and industry in Saxony are active in the field of artificial intelligence. Are you also interested in positioning your AI offering here? Then simply contact us.