Predict demand with AI-powered accuracy
Multi-model ensemble forecasting using LSTM, Prophet, XGBoost, and Transformer architectures.
Capabilities
aPlanner's AI forecasting engine uses LSTM neural networks, Prophet, XGBoost, and Transformer architectures — automatically selecting the best approach for each product and time horizon.
Multi-model ensemble forecasting
Multiple AI models compete — aPlanner automatically selects the best combination for your specific patterns. LSTM, Prophet, XGBoost, and Transformer architectures work together.
External signal integration
Go beyond historical data. Incorporate market indicators, economic data, commodity prices, and leading demand signals into every forecast.
Industry-specific intelligence
Yield-aware forecasting for semiconductor. BOM-aware for electronics. JIT-aware for automotive. Models built for your industry.
Hierarchical reconciliation
Forecasts that reconcile across SKU, product family, customer, and market levels — so everyone works from the same numbers.
Confidence intervals
Know not just what's predicted, but how confident the prediction is. Make better decisions about safety stock and risk.
Explainable AI
Understand why predictions are made. No black box — full transparency into the factors driving each forecast.
Technical Specifications
| Algorithms | LSTM, Prophet, XGBoost, Transformer Ensemble |
| Forecast Horizons | 1 day to 24 months |
| Granularity | SKU, Customer, Region, Channel |
| Data Requirements | Minimum 12 months historical (24 months recommended) |
| External Signals | Market indices, commodity prices, economic indicators |
| Accuracy Metrics | MAPE, Bias, Tracking Signal |
Transform your demand forecasting
Schedule a personalized demo and see how aPlanner can transform your demand forecasting accuracy.
Request your personalized demo