AI Models
Four engines, one mission
We benchmarked dozens of architectures. These four made the cut.
★ Best
Random Forest
Production prediction
82.3%
Accuracy
- Robust to noise
- Feature importance built-in
- Low overfitting
XGBoost
Edge deployment
79.8%
Accuracy
- Fast training
- Handles missing data
- Regularized boosting
Artificial Neural Net
Complex interactions
76.5%
Accuracy
- Non-linear patterns
- Scalable
- Multi-output
Hybrid Ensemble
Critical alerts
81.5%
Accuracy
- Combines top models
- Reduces variance
- Higher reliability