Smarter forecasting. Less food waste.

The Eaternity Forecast AI system represents a breakthrough in foodservice demand prediction, combining cutting-edge machine learning with deep domain expertise in restaurant operations.

Core Architecture Components:

• Transformer architecture with multi-head attention mechanisms for pattern recognition
• Long Short-Term Memory (LSTM) layers for sequential data processing
• Multi-layer processing of temporal patterns and seasonal variations
• Integration of weather forecasts, local events, and holiday calendars
• Real-time learning capabilities that improve with each prediction cycle
• Confidence intervals and uncertainty quantification for all predictions

Input Data Processing:

• Historical sales data normalized across time periods and menu items
• Weather data including temperature, precipitation, and seasonal patterns
• Local event calendars and public holiday information
• Day-of-week and time-of-year cyclical patterns
• Special promotions and marketing campaign data
• External factors like school holidays and local business cycles

Model Training and Validation: The system is trained on anonymized data from hundreds of restaurants across different cuisines, sizes, and geographic locations. Continuous validation ensures consistent performance across diverse operational contexts.

# Example prediction confidence output
{
  "dish_name": "Beef Bourguignon",
  "predicted_demand": 42,
  "confidence_interval": [38, 47],
  "confidence_level": 0.85,
  "factors": {
    "weather_impact": -2,
    "seasonal_factor": +3,
    "event_factor": +1
  }
}