Edge AI

Efficient AI for the future - on-device inference and training

Fast, private, energy-efficient, close to sensors, self-learning, mobile

Whether for automating processes or analyzing large volumes of data: Intelligent and self-learning systems are becoming increasingly important in business processes. Until now, these intelligent systems have always had to be connected to a cloud, as this provides the necessary computing power for AI models. With Edge AI, short for Edge Artificial Intelligence, the next generation of intelligent systems is now entering the home: intelligence is being transferred directly to the end devices.

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embedded world 2024

From April 9 to 11, 2024, the entire team will be at embedded world 2024.

Hall 4-422

Perhaps you visited us there and had interesting conversations, or are generally interested in our technology. Do not hesitate to contact us if you would like to stay informed about our training program or get in touch for a more detailed exchange.

We look forward to seeing you!

Our Service Offer

Research and Development

We offer you partial or complete R&D services.


  • Embedded AI: development tool for developing embedded AI solutions to reduce costs and improve the quality of your application.
  • Optimized AI model for your hardware: a tailor-made solution adapted to your hardware with optimized performance through AI.
  • Mentoring : We accompany you in your R&D projects from data acquisition to the development of an AI model.


We advise and support you with your individual concerns relating to your AI solutions.



  • Potential analyses: We carry out a quick potential analysis of your personal concerns.
  • Directional decisions: We provide you with groundbreaking support by creating an automated report to help you make initial directional decisions on your personal project.
  • Hardware recommendations: We advise you on suitable hardware and give you recommendations for use in your AI solution.
  • Personal support: Our interdisciplinary team and the network at IIS will support you with your personal project.


We may have already developed the right AI model and this can be integrated directly into your use case or licensed by you.


We optimize your application through standardized processes and extensive automation of time-intensive work specifically adapted to your use case.

Through training and automatic reduction of complex AI models by removing redundancies, we generate optimal AI models in terms of accuracy and efficiency.

We support you with rapid integration!

Certified Training

We provide you with a quick introduction to AI solutions. Our range of training courses includes AutoML webinars, skills training and seminars on various AI topics.


We would be happy to use your data for a customized seminar!

Contact us!

We realize the efficient processing of your R&D projects, as well as the training of junior staff with this new competence profile.

Contact us
for an individual consultation at


Benefits of Edge AI

Energy Efficiency and Resource Conservation

The TinyML needs up to a thousand times less power to run ML applications compared to a standard GPU. The reason for this is, among other things, the local execution of the models instead of sending the data back and forth. For this reason, the TinyML devices can run for years without batteries, depending on the use case.

The size of the batteries required and thus the use of valuable resources is also reduced due to the considerable energy savings.



Since the model is run locally, in order to perform inference, the raw data does not need to be sent to the cloud first and then sent back when processed. This reduces output latency as well as communication bandwidth requirements, which in turn enables rapid response.

Independence, Privacy and Security

The user is not dependent on a cloud service provider. Since the data does not have to be shared with external parties, this point ultimately also contributes to the protection of privacy.

In addition, there is no dependence on a communication link. The risk of possible interference during transmission between the embedded system and the cloud is therefore eliminated.

Overview of concrete services

We offer complete packages that can be used as a whole or in components according to your requirements. All components can be combined in any way and adapted to your needs.

We have very good experience with our customers in so-called "Fast Track Joint Labs": Together with you we develop a first solution for your embedded AI application within one month.

Typically the process is as follows:

  • Kick-Off
  • Selection of the required components of the solution
  • Fast Proof-of-Concept 
  • Box stop meeting and review
  • Joint development of the final AI application

As a result, an executable solution is created and the know-how is exchanged during the project.

What do you get?

  • We guide you quickly through a joint project to the finished AI pipeline in C/C++ or Python
  • Jointly developed software components enable you to replicate the development process

If you already have a data set, a proof-of-concept can emerge after just a few days.

Your benefits

  • Know-how transfer happens during the project, not afterwards
  • Your employees become AI experts for processing your applications (integrated training).

Some of our customers increasingly rely on AI functions in their products. To enable them to act independently, we provide a software suite with which our customers can develop, evaluate and deploy embedded AI pipelines themselves.

What do you get?

  • Software suite in the form of coordinated Jupyter notebooks and libraries developed by Fraunhofer in the background.
  • Export of final AI pipelines for embedded systems.
  • Adaptation of the software suite to your problems, e.g. processing of specific data sources (sensor data, audio, video)
  • A half-day introductory workshop, if possible on the basis of your own data


  • We recommend the combination with the seminar to build up extended know-how.
  • Support for one year, if necessary also incl. development hours
  • We are also happy to support you during the final integration, e.g. in the form of a joint lab (see on the right side)

Your benefits

  • Enormous know-how transfer through best practices implemented in the software suite
  • Immediate ability to act in your AI projects
  • We do not leave you alone in your projects

We offer a two-day Zero-to-Hero seminar in order to be able to implement the basics of machine learning in a practical way. The seminar can be tailored to you with the help of your data, if you want further training for your organizational unit.

What do you get?

  • With your data and wishes, we create an adapted version of our proven ML Seminar.
  • Your participating employees will learn the basics of machine learning including best practices in theory and with practical examples.
  • You will receive the seminar materials including the source code used (Jupyter notebooks).

Your benefits

  • Quickly build up knowledge in your own team
  • Knowledge that can be put into practice immediately

Potential analysis of your problem / your data set as report answering the following questions:

  • How well is your problem solvable?
  • Which AI processing chains meet your requirements?


What do you get?

  • Overview of power requirements / computational demand vs. achievable performance of AI pipelines on embedded hardware.
  • The report contains an overview of Pareto-optimal solutions with both classical ML and Deep Learning.
  • → How to decide:
    • Is there a compelling need for Deep Learning?
    • On which hardware does a solution fit best?

Your benefits

  • Quick assessment of the feasibility on your hardware
  • Early information on hardware decisions

Use Cases


From agriculture and biodiversity to people counting.

AI analysis directly behind the camera sensor enables numerous new applications without sending a lot of raw data to the cloud. Privacy remains protected at all times.


Condition Monitoring

Using machine learning in embedded systems to monitor the status of systems and machines in order to be able to react at an early stage or increase efficiency.


We've all been there: long queues at the checkout again.

With privacy-protecting AI on edge devices, seamless shopping is already possible.

This leaves more time for the finer things.



Machine learning in embedded systems, e.g. wearables for sports applications such as fitness, soccer, boxing or basketball.


Be it drones for remote sensing, AGVs in intralogistics or agricultural robots.

Mobile, autonomous robots require a powerful yet energy-saving AI for particularly long operating times.



Machine learning in embedded sensor modules for cognitive hand tools to recognize assembly processes and ensure quality.

© LZE GmbH