In Cryo-EM, high resolution of up to 2.2 Å data became available only very recently, and these advances led to the 2017 Nobel Prize in Chemistry. Cryo-EM can solve structures from 100 kDa up to several MDa, requires only a small amount of sample, and does not depend on crystallization. As cryo-EM maps have a higher information content than X-ray data, they should, in principle, be superior to electron density maps of comparable resolution. However, atomic models are currently fitted to reconstruction maps using restraints and parameters originally developed for crystallography, which limits the answers we can obtain from the new high resolution data as the underlying assumptions are not always justified. We develop tools directly based on the nature of the cryo-EM experiment, such as the neural network Haruspex, to overcome these challenges.