YieldGuard reads sensor data from your machines, spots degradation patterns invisible to the naked eye, and gives your maintenance team a full 24-hour warning — before a breakdown brings your line to a halt.
Just as a doctor reads vital signs to catch illness early, YieldGuard reads your machine's sensor signals to detect wear, stress, and abnormal behavior — before anything breaks.
Upload a CSV from your historian or PLC — or use the quick-try panel to enter current readings manually. No setup, no integration needed.
The model computes statistical fingerprints across vibration, temperature, pressure, current, RPM, and acoustics — looking at trends, spikes, and frequency signatures.
A clear risk score with an action: schedule maintenance, dispatch crew, or keep monitoring. No jargon, no false alarms — just what you need to know.
The AI model is downloaded once and runs locally. No sensor readings ever leave your device.
196-feature computation and tree-ensemble scoring happen client-side — no API call, no waiting.
Plain-English risk factors tell you exactly which sensor triggered the alert and in which direction.
LightGBM + XGBoost ensemble, trained with time-series expanding cross-validation (no data leakage), Optuna Bayesian HPO, isotonic calibration for honest probabilities, and PSI drift monitoring in production.
Explore the demo with 5 pre-loaded machines, or upload your own sensor CSV and get an instant 24h failure prediction.