Horizon • Causal Demand Forecasting
Patterns break.
Causality endures.
Traditional forecasts extrapolate patterns—until the pattern breaks. Horizon models the causal drivers, so forecasts adapt when conditions change.
30%
Accuracy gain
$5M+
Annual savings
24/7
Live updates
24-Hour Demand Forecast
Updating in real-time
Forecast
Actual
1000MW750MW500MW250MW0MW
00:0006:0012:0018:0024:00
Forecast Accuracy
94.3%MAPE: 5.7% • Updated 2 minutes ago
When patterns break, forecasts fail
Pattern-based models can't explain why demand changes—so when conditions shift, they're blind
Traditional Time-Series
- ✕Extrapolates historical patterns
- ✕No understanding of drivers
- ✕Breaks when conditions change
- ✕Cannot simulate scenarios
- ✕Black box predictions
Example:
"Demand forecast was 15% off because of unexpected policy change. No way to have known."
Horizon Causal Forecasting
- ✓Models causal relationships
- ✓Understands what drives demand
- ✓Adapts when conditions change
- ✓Simulates what-if scenarios
- ✓Fully explainable predictions
Example:
"Policy change detected. Horizon adjusted forecast based on causal impact. Accuracy maintained at 93%."
Horizon sees what drives demand
Every forecast is backed by a causal model showing which factors truly matter
Built for demand-driven industries
⚡
Energy Utilities
Grid operators, distribution planning
🛒
Retail & CPG
Inventory optimization, supply chain
🏭
Manufacturing
Production planning, capacity management
Forecast with confidence.
Plan with certainty.
See how Horizon delivers causal forecasts that adapt when conditions change.