We built Melon to reduce the friction between having data and actually doing something useful with it.

You upload a dataset, describe the problem in plain English, and Melon explores the data, surfaces patterns, and builds a personalized ML model trained on your data. You can also request an analysis of your data catered to a specific topic of your choosing.

Some of the use cases we’ve been exploring include sales optimization, retention/churn modelling, candidate-fit analysis, support trend classification, forecasting, anomaly detection, and turning messy spreadsheet exports into interactive decision tools.

Still early, but we’d love blunt feedback on where this feels useful, where it doesn’t, and what you’d want to see improved.