Train sklearn models (MLP, Random Forest, Linear Regression), export weights to JSON, and generate pure TypeScript inference code with zero npm dependencies. Handles the full pipeline: feature engineering, synthetic data generation, model training, weight export, and TypeScript codegen. The resulting model runs server-side (Node.js/Next.js) or client-side (browser) in <1ms with a ~10-50 KB weights file. No Python runtime, no ONNX, no TensorFlow.js needed at runtime.