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Supply Chain Optimization Engine

Price volatility, supply uncertainty, demand unpredictability – our models empower you to navigate even the most challenging supply chain scenarios armed with AI-powered, prescriptive recommendations.

High stock levels, lost sales and burdensome manual processes are costly consequences of an inadequate inventory management process. With targeted automation and AI-powered recommendations, we empower you to optimize your inventory levels, reduce costs, and deliver a seamless distribution service.

Our bespoke approach to forecasting demand

Off-the-shelf forecasting solutions use simplified mathematical and demand distribution assumptions that fit the average case – not your specific case. This generates recommendations based on unstable historical events and low forecasting reliability. Instead, at Rewire, we apply machine learning algorithms to perform bottom-up and top-down demand modelling. This allows you to explore supply chain scenarios and their cost implications in a highly detailed and accurate way. From accounting for outliers to planning for peaks in demand for new products. 

Scaling AI across your entire supply chain

Our supply chain optimization engines are developed using cutting-edge prefab components that we rapidly configure and customize in alignment with your strategy and circumstances. This approach means you can start experiencing value fast, and we can scale your AI deployment rapidly. In a few months, you could expand from a solution covering one product in three countries to 10 products across 30 countries. 

With our AI-generated recommendations, your supply chain managers can better forecast stock shortages, adjust inventory levels, and manage your logistics network with data-driven proficiency.

Our track record speaks volumes

4%

Increase sales revenue

Year one revenue increase of 4%, generating €16m through AI-powered forecasting.

19%

Improvements in forecasting

A prediction accuracy increase of 19%, delivering a €9m year one cost reduction through algorithm-based inventory levels.

18%

Reduction in working capital

Year one working capital reduction of 18%, driven by a 20% reduction in inventory costs, while maintaining stock availability.

What if we said, you could use data and AI to accurately predict expected demand distribution and calculate the cost implication of a whole variety of supply chain scenarios?
We can.
Ask us how
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