Silvi.ai was founded in 2018 by Professor in Health Economic Evidence, Tove Holm-Larsen, and expert in Machine Learning, Rasmus Hvingelby. The idea for Silvi stemmed from their own research, and the need to conduct systematic literature reviews and meta-analyses faster.

 

The ideas behind Silvi were originally a component of a larger project. In 2016, Tove founded the group “Evidensbaseret Medicin 2.0” in collaboration with researchers from Ghent University, Technical University of Denmark, University of Copenhagen, and other experts. EBM 2.0  wanted to optimize evidence-based medicine to its highest potential using Big Data and Artificial Intelligence, but needed a highly skilled person within AI.

 

Around this time, Tove met Rasmus, who shared the same visions. Tove teamed up with Rasmus, and Silvi.ai was created.

 

Silvi uses AI to increase the speed of collecting and analyzing published data to created meta-analyses and systematic literature reviews. When using Silvi, the researcher still makes all the scientific decisions, but with AI supporting data extraction, the speed of doing meta-analyses increases immensely. Silvi is directly connected to literature engines to ensure that the results are always up to date. These core qualities of Silvi ensures a tool that quickly helps you create high quality evidence that stays relevant.