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Artificial Intelligence at the Edge.

Embedded Systems Solutions.
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Moving data processing closer to the data source, i.e. edge computing, has many advantages and is often necessary for various reasons. For example, when larger amounts of data are involved (e.g. image data) or external cloud services cannot/should not be used for reasons of data security.

Why "AI at the Edge"?

"AI at the Edge" offers you the following advantages:

  • Real-time processing: Immediate on-site data analysis and decision-making for faster response times.
  • Data protection and security: Local processing reduces the transmission of sensitive data via networks, strengthens data protection and minimises security risks.
  • Increased efficiency: Targeted transmission of relevant data reduces data traffic, resulting in more efficient use of resources.
  • Robustness and resilience: Local processing ensures system robustness and resilience, independent of centralised cloud servers.
  • Adaptability: Local data interpretation enables adaptive and context-sensitive adjustment to changing conditions and requirements.

However, just like the edge system itself, the software and algorithms themselves must be highly integrated and efficient in order to be able to make the right decisions at the right time.

Our Methods.

Our team specialises in precisely this optimisation and the integration of data processing algorithms and artificial intelligence (AI) for and in edge systems and supports you in the following areas:

  • Model optimization: Reduction of model size and complexity for resource-efficient execution on edge devices.
  • Federated learning: Local training of AI models without transferring sensitive data to central servers.
  • Security protocols: Implementation of robust security mechanisms to protect data integrity, confidentiality and authentication at the edge.
  • Edge management platforms: Efficient platforms for monitoring, updating and managing AI models in distributed edge environments.
  • Edge development frameworks: Special frameworks to simplify the development, optimisation and integration of AI applications at the edge.

Areas of Application & Success Stories.

The areas of application for edge AI are diverse. We work with image data as well as classic sensor data ... Below you will find details of applications that we have already successfully implemented for our customers:

Tech Stack.

Artificial Intelligence
Hardware Vendors

Do you have a specific inquiry or would you like to find out more about us?

Don't hesitate and let's talk about it!