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AI-Enabled Replenishment

AI-Enabled Replenishment

An AI-enabled replenishment engine drafts orders across your network every week, ready for your planners to review and approve.

How it works

Every week Vintaflow works through your network and drafts the orders that keep each warehouse between its target and maximum levels. It starts from the ML demand forecast, current stock, inbound orders, and the lead time on each lane, then applies your rules: minimum order quantities, review periods, container capacity, and maximum coverage.

Joint replenishment looks across the whole portfolio instead of one item at a time, so products that ship together are planned together. When several suppliers can fill the same demand, the engine splits it by what each one can actually deliver.

The engine proposes, planners decide

Recommended orders land in a review queue. Planners accept, change, or decline each one, or approve a batch at once. Approved orders then move through the same order lifecycle as every other order, from placed to received, with every change recorded.

What it changes

  • A buyer reviews a drafted order each week instead of building it from a spreadsheet.
  • An importer fills each container with the products that need to move, within the lane's capacity.
  • A planning team sees shortfalls inside lead time while there is still time to act.

Frequently Asked Questions

Is replenishment in Vintaflow automated?
Vintaflow drafts recommended orders automatically every week. Planners review them and accept, change, or decline each one, so no order is placed without a person approving it.
Which constraints do recommended orders respect?
Minimum order quantities, review periods, target and maximum coverage, the lead time on each lane, and the container capacity of each lane.
Can Vintaflow plan orders across many products and suppliers?
Yes. Joint replenishment groups recommendations across your product portfolio, and when several suppliers can fill the same demand, Vintaflow splits it by what each supplier can deliver.

Next Step

Bring your current planning model into the conversation.

Tell us which part of the supply chain this feature would affect first and we can work outward from there.