Demand Forecasting

Harness the future of market demands with AI-driven precision to optimize inventory and production.

Ride the trend, before the trend becomes "the trend".

Our technology is:

Menhir’s Explainable AI provides transparency in demand forecasting processes, enabling businesses to understand and trust the predictive insights about market trends and consumer behaviors.

By identifying the causal relationships between market events and consumer demand, Menhir’s AI helps companies anticipate market needs more accurately, preparing them for fluctuations before they occur.

Menhir turns forecasts into actionable strategies, allowing companies to align their inventory and production plans with predicted market demands efficiently.

Action core

Decision Apps

Menhir's Decision Apps integrate real-time market data and consumer insights to dynamically adjust demand forecasts, helping businesses stay agile in rapidly changing markets.

Data & Model core

AI Models & Algorithms

Our cutting-edge, proprietary AI algorithms process vast amounts of internal and external data to predict future demand with high accuracy, supporting better stock management and reducing wastage.

Data Collectors & Data Fabric

Menhir’s Data Fabric compiles and processes data from various sources, including sales transactions, market trends, and consumer feedback, to create a detailed demand projection.

Menhir’s impact in Demand Forecasting

Menhir transforms supply chain management with predictive insights that ensure right-sized inventory and optimized resource allocation

Seasonal Demand Prediction

Adjust production and inventory management for clothing lines based on predictive analysis of fashion trends and seasonal variations.

Dynamic Stock Adjustment

Utilise real-time sales data and market signals to dynamically manage stock levels, ensuring optimal availability and turnover.

Supply Planning

Coordinate production schedules and inventory levels to align with anticipated market demands for new tech product releases.

Build Tomorrow, Today.

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