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
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.
Agent
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.
Watches every feed the twin ingests — WMS transactions, IoT sensors, labour clock-ins — and measures the indicators that lead problems, not just the ones that report them. Compliance drift gets flagged before it becomes an audit finding.
Agent
The Analyst
Your data guru. Drills into cost drivers, productivity issues and demand patterns, runs root-cause analysis, and alerts you when trends change.
Turns raw events into answers: which cost drivers moved, where productivity leaks, how demand is shifting. Root-cause analysis with the query trail attached, and an alert the moment a trend breaks pattern.
Agent
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.
Plans the operation forward — labour capacity, dock and resource schedules, SKU placement — against the volumes the forecast says are coming, so Monday starts with a plan instead of a scramble.
Interface
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.
Type the question the way you'd ask a colleague — "picking rate by zone last week", "which SKUs should move before peak" — and get charts, tables and KPIs computed live from the twin, not a canned report.
Engine
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.
Slotting, batching and scheduling have more combinations than any team can evaluate. The engines search the full solution space against your real constraints and return the plan with the maths — in hours, not consulting weeks.
Engine
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.
Plans replay against months of your real orders in the twin, and each what-if returns its delta against baseline — cost, travel, throughput. If the numbers do not beat the incumbent, the plan never reaches the floor.
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
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.
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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.
Frequently asked questions
What WareBee AI does, how it stays accountable, and how your team stays in control.
What is WareBee AI and what does it cover?
WareBee AI plans, analyses and optimises your warehouse from a digital twin built on your own data. It shows up across six layers: an AI chat over your data, optimisation engines for the hard problems, analysis and process mining, plan generation from forecasts, what-if simulation, and continuous audit.
Why does WareBee say its AI shows its work?
Because every recommendation arrives with the evidence. Before WareBee proposes a move, it simulates the change in your digital twin against your real orders and attaches the result — travel saved, throughput gained, cost avoided — so your team reviews measured numbers, not a black box.
What is Ask AI?
Ask AI answers plain-language questions about your operation, such as picking rates by zone or which SKUs to move before peak, and returns charts, tables and KPIs behind every answer. It is grounded in your digital twin, so the response reflects your warehouse rather than an average one.
Which problems do the optimisation engines handle?
Slotting, batching and scheduling are NP-hard — far too many combinations for a person or a rules engine to work through. WareBee's engines search the full solution space and return a tested plan in hours rather than weeks.
Does WareBee AI make changes without my team approving?
No. People stay in the loop by design: WareBee proposes, your team decides, and approved recommendations flow back to your WMS for execution. Nothing about how your people work has to change, and the reported saving is 10-15% of operational costs.
How do I start with WareBee AI?
Start with a paid pilot on your own data. Layout, locations, items, stock and order history flow in through the Universal WMS API — REST, scheduled exports or a simple CSV — and become your digital twin, so you judge the AI by what it finds in your warehouse.