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WareBee

AI Slotting

Every SKU.The right location.

WareBee's AI slotting engine re-slots your warehouse from a digital twin of your layout, stock and orders — improving throughput and resource utilisation without new hardware.

Start re-slotting
Warehouse layout after AI slotting optimisation in WareBee with every SKU placed to minimise travel and congestion

Strategic and tactical slotting, one engine

Use strategic (macro) slotting to set the shape of your warehouse — zones, velocity bands, family groups. Use tactical (micro) slotting to keep it sharp week after week.

The WareBee Dynamic Optimisation engine delivers optimal results in just a few hours.

  • Macro slotting for seasonal and structural change
  • Micro slotting for continuous improvement
  • Before and after comparison for every run
See the Optimise module
Strategic and tactical AI slotting runs compared before and after in WareBee, scored on travel and throughput

Slot for peak before peak arrives

Simulate demand scenarios in the digital twin and re-slot ahead of peak season instead of during it.

Every recommendation is scored on travel, congestion and utilisation, so you know the payoff before a single pallet moves.

Explore warehouse simulation
Peak-season demand scenario simulated in WareBee's digital twin ahead of an AI re-slotting run

Learn more

What is AI slotting?

Slotting is deciding where every SKU lives in your warehouse. AI slotting hands that decision to an optimisation engine that weighs demand velocity, item affinity, congestion, ergonomics and replenishment effort across thousands of locations at once — a problem far beyond spreadsheets.

WareBee runs slotting on your warehouse digital twin. The engine proposes moves, the twin simulates the result against your real orders, and you get a before-and-after comparison of travel, throughput and utilisation for every run.

Because re-slotting is cheap to evaluate, it stops being a once-a-year project. Slot strategically for the season, then let tactical micro-slotting keep the warehouse near optimal as demand shifts.