Rowan uses the fastsolv model developed by Lucas Attia, Jackson Burns, and co-workers at MIT and described in the preprint "Organic Solubility Prediction at the Limit of Aleatoric Uncertainty." (See also the authors' own fastsolv web interface.)
The fastsolv model was trained on BigSolDB, which contains 54,273 experimental solubility measurements spanning 839 solutes and 138 solvents across temperatures ranging from -30°C to 130°C.
Solutes and solvents are both input using the SMILES format, and the model is used to generate a prediction for each solute-solvent-temperature combination. Rowan has a number of solvents predefined on the front-end, each of which is associated with a SMILES string, and supports custom SMILES entry.
This workflow returns both predicted solubilities and standard deviations for each solvent-temperature combination. When viewed on Rowan's web GUI, these results are plotted on an interactive graph.