Question 1

What is causal demand forecasting?

Accepted Answer

Causal demand forecasting uses causal AI to identify the true drivers of demand,promotions, pricing, weather, economic indicators, and competitive actions. Unlike time-series methods that extrapolate past patterns, causal forecasting understands WHY demand changes.

Question 2

How is it different from time-series forecasting?

Accepted Answer

Time-series forecasting relies on historical patterns that break down during supply shocks, new product launches, or regulatory shifts. Causal forecasting identifies the underlying causal mechanisms, producing forecasts that remain accurate even when conditions change dramatically.

Question 3

What data sources does Horizon use?

Accepted Answer

Horizon integrates with ERP systems, POS data, weather APIs, economic data feeds, promotional calendars, and competitive intelligence sources. It automatically aligns heterogeneous data and identifies which sources are causally relevant.

Question 4

Which industries does Horizon serve?

Accepted Answer

Horizon serves energy utilities, retail and CPG, manufacturing, and supply chain operations. Any industry where accurate demand forecasting drives significant business outcomes benefits from causal forecasting.

Question 5

How accurate is Horizon compared to traditional methods?

Accepted Answer

Horizon delivers up to 30% improvement in forecast accuracy versus traditional time-series methods. The improvement is most pronounced during regime changes, promotional periods, and supply disruptions,exactly when traditional forecasts fail.

Patterns break.
Causality endures.

See Horizon in Action

When patterns break, forecasts fail

Traditional Time-Series

Horizon Causal Forecasting

Horizon sees what drives demand

Built for Planning Teams

Energy Utilities

Retail & CPG

Manufacturing

Works With Your Systems

Forecast with confidence. Plan with certainty.

Patterns break.Causality endures.