Skip to content
WareBee

WareBee AI

Warehouse AIthat shows its work.

WareBee AI plans, analyses and optimises your warehouse from a digital twin built on your own data. Every recommendation arrives with the evidence — simulated, measured and ready for your team to execute.

See WareBee AI in action
WareBee AI digital twin dashboard — the foundation for AI agents, optimisation, forecasting and simulation

The AI team

One digital twin. A whole AI team.

WareBee's AI isn't a single black box — it's a team of specialised agents and engines, each grounded in the same digital twin of your warehouse.

The Scout

Your eyes on the floor. Monitors data feeds from WMS and IoT, tracks leading and lagging indicators, and flags compliance issues before they become findings.

The Analyst

Your data guru. Drills into cost drivers, productivity issues and demand patterns, runs root-cause analysis, and alerts you when trends change.

The Coach

Your team's biggest supporter. Plans labour capacity, schedules resources and dock doors, and optimises SKU placement for the volumes that are coming.

Ask AI

Plain-language answers about your operation — picking rates by zone, SKUs to move before peak — returned as charts, tables and KPIs grounded in the twin.

Optimisation engines

Slotting, batching and scheduling are NP-hard problems — too many combinations for a human or rules engine. WareBee's engines search the full solution space in hours.

Predictive simulation

Every plan is tested in the digital twin before the floor sees it — demand spikes, layout changes, shift patterns, even automation what-ifs.

Recommendations with receipts

Trusting AI with a live warehouse takes more than a confident interface. Before WareBee proposes a move, it has already tested it: the change is simulated in your digital twin against your real orders, and the result — travel saved, throughput gained, cost avoided — comes attached.

Your team reviews the evidence, approves the change, and your WMS executes it. Nothing about how your people work has to change.

  • Every recommendation simulated before you see it
  • Before-and-after comparison for every run
  • Your team approves, your WMS executes
See AI slotting
WareBee AI recommendation with simulated evidence — before and after KPIs the team reviews before approving

Ask your warehouse anything

"What are our picking rates by zone?" "Which SKUs should move before peak?" "Where did Tuesday's overtime come from?" Ask AI answers in plain language, with charts, tables and KPIs behind every answer.

It isn't a generic chatbot — every response is grounded in your digital twin, so the answer reflects your warehouse, not an average one.

Explore warehouse analysis
Ask AI in WareBee answering a plain-language question about picking rates with charts grounded in the digital twin

Learn more

How does WareBee AI work for warehouses?

It starts with your data, not ours. Layout, locations, items, stock and order history flow in through the Universal WMS API — REST, scheduled exports or a simple CSV — and become a digital twin: a simulation-ready copy of your warehouse.

AI shows up across six layers of the platform. Ask anything (AI chat over your data). Solve the hard problems (optimisation engines for slotting, batching and scheduling — genuinely NP-hard decisions). Understand the past (analysis, BI and process mining). Generate the plan (labour, allocations and zoning from demand forecasts). Test before you commit (what-if simulation in the twin). Keep it honest (continuous audit of storage, process and decisions).

People stay in the loop by design: WareBee proposes, your team decides, and the recommendations flow back to your WMS for execution — saving 10–15% of operational costs. Start with a pilot on your own data and judge the AI by the only measure that matters: what it finds in your warehouse.