Automated Quality Assurance with Edge ML

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There are many advantages to using Edge ML – offline machine learning – to optimise your business processes. Automation in Quality Assurance is one of them, where the return on investment is tangible and promising.  With this technology, you can ensure a consistently high level of quality for your products or services, while saving in cost.

In this Virtual Tech Update, we will share our hands-on experiences with offline machine learning,  including a case from Velux where we illustrate the clear benefits and rationale behind the solution, followed by a practical review of the integration with Azure Stack Edge.

We will cover the following topics:

  • How to maintain a high level of security for your applications
  • How to minimise dependencies on your central systems
  • How to  ensure decisions and actions are computed in due time
  • Different deployment scenarios

This event is aimed at:

  • CDO, CIO, CTO’s
  • Business developers and leaders
  • Strategic business advisors

Nicholai Stålung

Trifork

Data Scientist and Machine Learning Expert

Nicholai Stålung has a background in econometrics, mathematical modelling and financial technology. He currently work as a data scientist and machine learning consultant at Trifork Copenhagen.

Julie Bork Nellegaard

Trifork

Moderator and Design Thinking Expert

Julie Bork Nellegaard is Design Thinking expert at Trifork, where she facilitates workshops with clients across different Trifork locations and markets. Julie has a broad experience with Design Thinking applied in digital innovation and business development. Her key role as facilitator is to ensure a user-centred approach end-to-end and to drive the process towards the best solution across business, IT and design.

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