This study extends the GNNIS approach to 39 organic solvents and presents a workflow for rapidly identifying Boltzmann-weighted conformational ensembles of small molecules in solution in combination with standard force fields. The GNNIS model was trained on a diverse set of small molecules simulated in the 39 different solvents, validated based on prospective MD simulations, and tested on conformational preferences determined from NMR experiments. Both comparisons show excellent agreement of the method and the reference data. Further, the dramatic speed-up compared to explicit-solvent simulations (i.e., ensembles can be generated within minutes rather than days) makes the proposed approach a powerful tool for understanding the behavior of molecules in solution. This advance could facilitate the rational design of molecules by enabling the study of larger datasets and faster turnarounds, as well as the accurate and fast interpretation of experimental observables. The software is provided open-source, and the training data is made freely available.