WaveForecaster
Time-Series Prediction
That Actually Works
Wave-equation-based time-series forecasting. 37% lower MSE than LSTM with 4x fewer parameters. Built for production workloads where accuracy and efficiency both matter.
Benchmark Results
Validated against standard baselines on common forecasting benchmarks.
| Property | LSTM | Transformer | WaveForecaster |
|---|---|---|---|
| MSE (normalized) | 1.00 | 0.92 | 0.63 |
| Parameters | 1.00x | 1.2x | 0.25x |
| Training time | Sequential | Parallel | Parallel |
| Long-horizon decay | Severe | Moderate | Minimal |
| Multivariate | ✓ | ✓ | ✓ |
Target Applications
Financial Forecasting
Stock prices, volatility, risk metrics. Lower MSE means better risk management and more profitable signals.
Energy Load Prediction
Grid demand, renewable output, pricing. 37% less error directly reduces over-provisioning costs.
Supply Chain
Demand forecasting, inventory optimization, logistics planning with fewer parameters → faster retraining on new data.
IoT / Sensor Streams
Predictive maintenance, anomaly detection. Real-time inference on resource-constrained edge hardware.
Climate & Weather
Multivariate physical systems with long temporal correlations. Minimal long-horizon decay maintains accuracy.
Healthcare Monitoring
Patient vitals, disease progression, readmission risk. Where accuracy saves lives and reduces cost.
Join the early access program
WaveForecaster is currently in private preview. We're working with select partners to validate on real-world forecasting workloads.