The full answer
Machine learning differs from generative AI. Instead of producing text, a predictive model learns patterns from your historical data to estimate what is likely to happen next, such as which customers may leave, which orders may be late or which readings look abnormal.
Projects begin with the data. Creuto assesses what records you hold, how complete and reliable they are and whether they contain enough history to learn from. Sometimes the first deliverable is a data pipeline and dashboard, with models following once the foundation is in place.
Models are evaluated against held-out data and compared with simple baselines, so you know whether the model genuinely improves on current methods. Results are explained in business terms, not just technical metrics.
In production, models need monitoring because the world changes. Creuto tracks prediction quality and data drift and retrains models on a schedule or when performance drops.
Aquapulse, an aquaculture intelligence platform used by 6,000+ farmers across 150+ villages in Odisha, Andhra Pradesh and West Bengal, shows how data-driven insight can reach users in the field.