Overproduction leads to inventory losses, while underproduction causes missed revenue and dissatisfied customers. Traditional forecasting is limited by static data.
solution
Our Solution
We designed AI-powered demand forecasting models that use real-time data to align production with market needs.
Tools we used
Approach
Step-by-Step Workflow
Step 1
Collect sales, market, seasonal, and external data.
Step 2
ML models analyze demand patterns.
Step 3
Predict short-term and long-term demand.
Step 4
Adjust production schedules accordingly.
Quantifiable Benefits
Reduction in inventory wastage
%
Improvement in forecast accuracy
0%
Higher on-time delivery rates
%
Who’s Using This
Unilever, P&G (AI demand planning)
Automotive manufacturers
Consumer goods factories
Why It Matters
Accurate demand forecasting reduces waste, saves costs, and ensures customers get what they want, when they want.
case studies
Real Results. Real Impact.
See how these use cases helped industry leaders transform operations with AI & XR.