Up to 44% shorter
picking routes.

Every pick. Every route. Optimized.

Slotter uses real warehouse data to optimize SKU
placement and picking routes, working alongside
your existing WMS or ERP.

THE PROBLEM

Every unnecessary
step adds up.

Poor Slotting

High-frequency SKUs and products frequently picked together are not always stored in the most efficient locations. Poor slotting adds extra miles to every picking route.

Unoptimized Routes

Even with a good warehouse layout, pickers travel unnecessary distances when the picking sequence is not optimized.

More distance

More time

Higher picking costs

THE SLOTTER APPROACH

One optimization layer.
Two critical decisions.

Intelligent Slotting

Optimize SKU locations based on picking frequency, affinity, travel distance, location and SKU constraints.

Dynamic Routing

Optimize the picking sequence for each order independently to minimize total travel distance.

DATA-DRIVEN OPTIMIZATION

Warehouse data in. Optimized warehouse out.

Warehouse Layout

SKU Master Data

Historical Order Data

Picking Data

Distance Data

Warehouse Constraints

Optimization Engine

Frequency, topology and
distance modeled together.

Optimized Slotting Plan

Where products should be stored.

Optimized Picking Routes

Efficient sequence for picking locations.

SIMULATION BEFORE ACTION

Optimize before you move a single product.

Slotter can simulate recent orders against a proposed slotting plan and compare the resulting travel distance with the current warehouse layout.

18-44%

Reduction in picking travel distance

Measured in a real warehouse environment.

CURRENT LAYOUT

Current slotting creates longer picking routes and unnecessary travel.

PROPOSED PLAN

Slotter-optimized routes designed to reduce travel distance and picking time.

COMPATIBILITY

Built to work with any WMS.

WMS / ERP

WHS layout, SKU, order and movement
data remain in your existing systems.

Slotter

An optimization layer—it imports data
without taking over operations.

Optimization

Optimized slotting plans and picking
routes returned to your team.

Works with data from your existing WMS or ERP

Adds slotting and routing optimization

Keeps inventory and warehouse execution in your existing systems

Any WMS

API Data Exchange

Any ERP

File–Based Data Import

MEASURABLE OUTCOMES

Improvements you can
quantify.

Slotter uses historical orders and real
operational data to quantify expected
improvements—not generic industry averages.

Reduce picking distance

Data-driven slotting decisions

Better workforce utilization

Higher picking productivity

Lower picking costs

Shorter order picking time

WHO IT'S FOR

Built for warehouses where
every step counts.

The higher the picking volume and the larger
the warehouse, the more every mile saved matters.

Large distribution
centers

High-volume
warehouses

Different
industries

High-volume fulfillment operations

Warehouses with large SKU counts

Operations with high picking frequency

FAQ

Common questions about Slotter.

What is Slotter and how does it optimize?

Slotter is a warehouse optimization solution that uses operational data to optimize SKU placement and picking routes—reducing travel distance and picking costs while working alongside your existing WMS or ERP.

Can we simulate results before changing SKU locations?

Yes. Slotter replays historical orders against a proposed slotting plan and compares the resulting travel distance with your current setup before any products are physically moved.

Does Slotter replace our WMS or ERP?

No. Slotter works with data from your existing WMS or ERP. It analyzes the required data and returns optimized slotting plans and picking routes without taking over warehouse operations.

How long does implementation take?

Implementation time depends on warehouse complexity, data readiness, and the selected data transfer method. Once the required data is available, the first optimized plan can typically be produced within a few weeks.

What data does Slotter need?

Slotter requires historical order data, SKU master data, warehouse layout information, and relevant operational constraints.

What efficiency improvements can we expect?

Results vary by warehouse. In a real warehouse environment, Slotter reduced picking travel distance by 18–44%, supporting lower picking costs and higher productivity.

Up to 44% shorterpicking routes.

Every unnecessary step adds up.