03 / MACHINE LEARNING
AutoML Studio
Train ML models on your data — no data-science team required.
AvailableMost teams have prediction problems long before they have a data-science team: which customers will churn, which invoices will pay late, which leads will convert. AutoML Studio closes that gap. Upload a table, pick the column you want to predict, and it handles the rest — algorithm selection, training, and a fair evaluation on rows the model never saw.
What makes it different is how it reports back. Instead of a wall of metrics, every number comes with its meaning in plain English, benchmarked against simple baselines so you know whether the model is genuinely earning its complexity. Explore what-if scenarios to see exactly which factors drive a prediction, tune the decision cut-off to match your tolerance for false alarms, and act on suggestions like retraining without columns that aren't pulling their weight.
AutoML Studio is open source — the code lives on GitHub, so you can run it on your own infrastructure and keep your data where it belongs.
Capabilities
Plain-language results
No jargon walls. Every metric is explained in words — how often predictions were right, how well the model tells categories apart, and what to expect on new data.
Honest by construction
Rows are held back for fair testing, results are cross-validated, and the model is benchmarked against simple baselines — so you know when the extra complexity isn't earning its keep.
What-if scenarios
Adjust any input and watch the prediction update in real time, with a breakdown of which factors pushed the result one way or the other.
Tune the decision cut-off
Slide the confidence bar to trade off catching more cases against fewer false alarms — measured live on the held-back test rows.
Actionable suggestions
The studio flags columns that barely influence the model and offers one-click retraining without them — then lets you compare models to confirm nothing was lost.
Take the model with you
Download the trained model and a shareable report, compare candidate models side by side, or fine-tune and train another run.
A look inside
Interested in AutoML Studio?
Reach out for early access, partnership, or to learn more about where it's headed.