Submit what you know. Receive an endpoint that knows it too. We handle the model, the infrastructure, and the deployment — you focus on what the predictions mean.
POST https://cletus-service.onrender.com/predict/a3f2b1c9-4d71-...Task
Classification
Target column
churn_risk
Training rows
3,420
API Key
clts_••••••••••••••
Test in Browser
01
Define what you want to predict. Everything after — preprocessing, architecture, training, validation — is handled automatically.
02
The model learns from your specific labeled data. Tables train a network from scratch; image folders build on a pretrained vision network. Domain specificity is the point.
03
Every successful training run produces a secured REST endpoint. You get a key. You start calling it. That's the whole workflow.
01
Upload your labeled dataset — a table of the inputs your domain generates and the outcomes you care about, or a folder of images per class.
02
A model is built on your data, evaluated for accuracy, and prepared for deployment. No configuration on your end.
03
A secured API key and URL. Pass in new observations, receive predictions. Use it from any language or environment.
Most prediction problems don't need a machine learning team. They need the right tool and the right data. You have the data.
Start for free