Connect Bitlog WMS to WareBee.

How the connection works.

1. 1

   Get the data out

   Connect via REST API, scheduled exports, or a one-off CSV — whatever Bitlog WMS supports in your setup. No changes to your WMS configuration.

2. 2

   WareBee builds the twin

   The Universal WMS API maps your feeds onto the five core data types below and builds a live 3D digital twin of your warehouse.

3. 3

   Optimise and execute

   Analyse performance, simulate changes, and send approved recommendations — slotting, batching, labour plans — back to Bitlog WMS for execution.

What data WareBee reads.

Five data types cover everything the twin needs. Bitlog WMS already produces all of them.

• Events

  Picking, replenishment and putaway events with timestamps, users, locations and quantities.

• Orders & picklists

  Order lines, dates, quantities and routing metadata — waves, docks, priorities.

• Items

  SKU master data: dimensions, weight, unit-of-measure hierarchy, groups and stackability.

• Inventory & assignments

  Which SKU sits where, and in what quantity — the twin’s current state.

• Locations

  Aisles, bays, levels and positions with dimensions — the physical map of your warehouse.

Ask AI about your Bitlog WMS data.

Anyone on the team can ask, in plain language — answers come back as charts, tables and KPIs, grounded in the twin built from your Bitlog WMS data.

• “What are our picking rates by zone?” → Ask AI
• “Which SKUs should move before peak season?” → Ask AI
• “Where is travel time leaking in Bitlog WMS?” → Ask AI

Value for every slotting model.

However Bitlog WMS runs your warehouse — fixed slots, dynamic putaway or a mix — the twin optimises the part that matters.

• Static slotting

  Better slotting

  Every SKU gets the fixed slot that minimises travel and congestion, with re-slotting plans your team can apply week by week.

• Dynamic slotting

  Zone configuration

  WareBee tunes the zones themselves — velocity boundaries, putaway rules and zone shapes that direct stock to the right areas.

• Hybrid

  Both, together

  Optimised fixed pick faces where stability pays, optimised zone rules where flexibility wins — one model covering both.

What you unlock.

• Improve WMS slotting

  Optimal slot assignments, simulated in the twin and sent back to Bitlog WMS for execution.

• Batching & clustering

  Group orders into efficient pick waves that cut travel and picking stops.

• BI tools

  Warehouse analytics over your events — cost to serve, utilisation, CO₂, velocity.

• AI dashboard

  KPIs and trends assembled by AI, surfacing what changed and why it matters.

• Ask AI

  Plain-language questions about your data and processes, answered as charts and tables.

• Root-cause analysis

  Trace a missed SLA or a slow shift back to the events that caused it.

• Process mining

  Reconstruct how work actually flows — detours, rework and bottlenecks included.

• Master-data analysis & audit

  Find dimension gaps, orphan locations and data issues — then fix them in the WMS.