Xen.AI Supply Chain
Xen.AI Supply Chain - an Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning based customizable solution for supply chain management and price optimization.
Most of the companies will have the challenge of matching their supply volume to the customer demand. How well a company manages this challenge has a major impact on its profitability. The typical cost of carrying inventory is at least 10% of the inventory value. So, the amount of inventory held has a major impact on available cash. It is important for companies to keep inventory levels as low as possible and to sell inventory as quickly as possible. Studies have shown a significant correlation between overall manufacturing profitability and inventory turns.
In many cases we deal with multi-echelon structure of supply chain with a few upstream and downstream facilities combined in a complex network structure. Modeling and optimization of multi-echelon supply chain systems is challenging as it requires a holistic approach that exploits interactions between echelons while accurately accounting for variability observed by these systems. However, it provides the most effective solution for lowering overall inventory cost, and increasing safety stock levels across all of these echelons.
Xen.AI Supply Chain solution can be helpful to solve important problems in supply chain network and logistics, they include:
- Ability to predict optimal number of items to keep at a given stock to satisfy customer needs.
- Multi-echelon inventory optimization to minimize total system costs.
- Price optimization using Machine Learning with account of all possible factors.
- Managing logistical relationship between the supply chain nodes.
- Increase customer retention and the company revenue.
|For more information, please download the :|
|Brochure: Datasheet: Text Version|
|Please see our use case slides and demo applications:|
|Inventory Simulation and Optimization demo application|
|Logistics Optimization demo application|
|Logistics Optimization use case slides|