Scyfer, the Deep Learning Company
Scyfer helps companies to maximize value of big data by analysis of millions of variables and data points. Scyfer improved current predictive models by 5-20%, implementing Deep Neural Networks, a disruptive new powerful predictive model development in artificial intelligence. Scyfer is specialized in Deep Neural Networks and bridges the gap between the existing knowledge of machine learning in the academic world and the companies that want to benefit from vast amount of data. Scyfer B.V. is a spin-off from the University of Amsterdam.
Download company info: Scyfer Company Info.pdf
Our consulting services
Eur 470.000 Horizon 2020 grant accepted by the EU
Scyfer is proud to announce that the H2020 proposal in traffic data analysis is accepted by the European Union. Scyfer is part of a consortium that will apply state of the art machine learning technology to predict transport demand and supply in 3 European cities. More news will follow soon.
Tata Steel announces collaboration with Scyfer
On Friday 6th of November, Tata Steel opened a research office at the Amsterdam Science Park. Here, Tata Steel seeks to form new collaborations with other companies to stimulate innovation within Tata Steel. Scyfer is proud to be the first research partner of Tata Steel at the Amsterdam Science Park. Together, we will improve the steel inspection process by applying Scyfer’s state-of-the-art deep learning technology.
Scyfer receives Eur 217.000 grant for MRI medical image analysis
Scyfer will use the financial support to help develop their deep learning platform for analysing medical images to optimize processes in analysing 3D-MRI images. We use smart algorithms for automatic image recognition. The algorithms are able to detect patterns, which help to identify and highlight abnormalities making it easier for the specialist to diagnose. This technology will not only improve healthcare, additionally it can lover costs considerably, according to the FICHe committee.
“The FICHe funding helps us to speed up developments to launch our product in the health market. We focus on the working processes in diagnostic centra and then develop the technical solution that can bring real benefit in the day-to-day workflow of a radiologist. Our goal is to help speed up tedious and boring work so that the radiologist can spent more time on the complex cases. This saves valuable time, patients get quick results, reduces costs and makes work more interesting. We focus now on the relative simple cases with large volume and create buy in with the radiologists. After that we can co-develop more advanced support for their day to day work by applying more advanced deep learning technology.”