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Demand Forecaster Agent

Loads 24+ months of historical sales data. Applies time-series models (ARIMA, STL decomposition) to detect seasonality patterns.

Agent ID
demand_forecaster
Sector Value-Added Distribution (VAD) & IT Wholesale
Status
Operational

Problem Statement

The challenge addressed

Predicting future demand is complex due to seasonality, trends, promotions, and market volatility—leading to stockouts or overstock situations.

Core Logic

How the agent solves it

Loads 24+ months of historical sales data. Applies time-series models (ARIMA, STL decomposition) to detect seasonality patterns. Incorporates market trend adjustments. Generates SKU-level forecasts wi...

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