From Research to Cutting-Edge Technology!
Ekkono is a Swedish software company founded in 2016. It is based on the research by Rikard König, a PhD and Senior Lecturer in Machine Learning. He presented his work to serial entrepreneur Jon Lindén, who immediately fell in love with the idea of making IoT devices more intelligent. Together with Anders Alneng and Joakim Andersson, both previous co-workers to Jon, they founded Ekkono. Today, the company consists of a diverse team of experienced entrepreneurs, Machine Learning Engineers, Data Scientists and Embedded Developers. Together, we’re striving to make the earth a better place with technology.
Ekkono is born out of seven years of machine learning research. More precisely in the area of high performance computing and predictive analytics. The result is a resource efficient small-footprint solution which can run most applicable machine learning algorithms on small platforms. We deliver an edge computing platform for connected things packaged in a Software Development Kit.
The Edge ML Technology
Ekkono’s edge machine learning software runs onboard the devices such as vehicles, air conditioners and electrical motors. It enables smart, self-learning and predictive features. The traditional machine learning approach is to collect big data from many units over a long period of time. We usually approach the problems from another angle. We learn the normal behavior for an individual device. If something deviates from that normal, we will notice. And the more data we see, the better we get on making the machine learning model adaptive and more precise. With our solutions, your product will only get better with time.
Our toolkit facilitates use cases like:
- Predictive/Condition based maintenance
- Self-configuring products
- Performance optimization
- Entirely new business models
With Ekkono you can harmonize on one solution for all your edge machine learning needs.
The Internet of Things is a genuine transformation of how product companies do business. For example, it will enable consumption-based pricing, added-value services based on domain expertise, redefining the reseller chain, and more. But this can’t be done manually. It doesn’t scale. It requires automation.
The solution for IoT automation spells machine learning. The traditional approach to machine learning, however, where data is collected and processed in gigantic cloud-based data lakes, comes with too many problems and constraints. Ekkono solves this problem by using machine learning in a different way. Instead of looking for common denominators from many, we learn what’s normal for the individual device by running onboard the device – edge machine learning. In other words, we really do edge machine learning, not just edge inference. Our core business is about predictions, and this is happening now.