Patterns break.
Causality endures.
Traditional forecasts extrapolate patterns, until the pattern breaks. Horizon models the causal drivers, so forecasts adapt when conditions change.
Causal Demand Forecasting
Explore Platform
See Horizon in Action
Experience how Horizon delivers causal demand forecasting with explainable predictions that adapt to changing market conditions.
Active Parts
0
Stockouts (3 mo)
0
Stockouts (6 mo)
0
Expiring (3 mo)
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Expiring (6 mo)
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Demand Trend
Inventory Levels
Critical Items
Bearing Assembly
Part P-001
12d
Qty: 3
Hydraulic Pump
Part P-014
28d
Qty: 1
Control Module
Part P-027
35d
Qty: 2
Seal Kit
Part P-089
45d
Qty: 8
Drive Belt
Part P-112
52d
Qty: 5
1 critical and 2 warning items need immediate attention
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
Demand Forecast
847 MW
Industries
Built for Planning Teams
Energy Utilities
Grid operations and distribution planning
Retail & CPG
Inventory optimization and supply chain
Manufacturing
Production planning and capacity management
Integrations