TRAIN MACHINE
LEARNING
IN MINUTES
Upload a CSV. Pick a column. Watch five algorithms compete and rank themselves. Get a deployable model — no Python knowledge needed.
SIX STEPS. ONE TRAINED MODEL.
From raw spreadsheet to production-ready model — the entire pipeline takes under ten minutes.
Upload CSV
Drop any spreadsheet — sales, fraud, churn, health data. The system auto-detects every column and data type instantly.
Choose Target
Pick the column you want to predict. One click and everything else becomes an input feature automatically.
Run AutoML
Hit one button. Five algorithms compete in parallel — Random Forest, XGBoost, Gradient Boosting, and more.
Read Leaderboard
Get ranked results instantly. Accuracy, Precision, Recall, F1 — every metric shown with visual charts you can act on.
Test Predictions
Open the Predict tab and run the model against your own inputs in real-time. See which features drove each decision.
Export & Deploy
Download a ready-to-run ZIP: model binary, inference script, requirements, and a README. Deploy on any Python machine.
EVERYTHING YOU NEED. NOTHING YOU DON'T.
5 Algorithms in One Click
Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, and XGBoost — all trained and ranked automatically.
Visual Analytics Suite
Feature importance, ROC curves, grouped precision/recall charts, and accuracy comparisons — no BI tool needed.
Confusion Matrix
Full TP/FP/TN/FN breakdown with color-coded cells and derived metrics: Accuracy, Precision, Recall, Specificity.
Real-Time Prediction Sandbox
Type in any values and run the winning model live. Every prediction comes with a decision-factor explanation.
Secured Local Compute
All training and inference runs securely on your local server. Your data never leaves your secure system.
One-Click Export
Download a production-ready ZIP with model.pkl, predict.py, requirements.txt, and full usage instructions.