Warehousing
AI that understands how warehouses actually work.
Warehousing isn't a database problem. It's a human problem layered over a database. Our agents are built by people who spent two decades inside warehouse operations — so they know where to look.
The current state
The problem, honestly.
- The warehouse system knows state but not why things go wrong. When a delivery gets stuck or a wave fails, operators chase root cause across four screens and three people.
- Senior warehouse consultants carry the real knowledge. They are expensive, rare, and getting rarer as younger operators refuse to learn legacy stacks the old way.
- Generic AI copilots don't understand putaway strategies, exception queues, or why this particular site keeps running the same issue at 4am.
Our approach
How we think about it.
- Build a narrow agent — Smart Warehouse — that does one thing well: warehouse diagnostics. It lives next to your WMS with read-scoped access and proposes actions a human signs off on.
- Give it three-tier memory: episodic for the session, case for related past issues, site for the warehouse's personality. The agent compounds over months.
- Govern every write. Smart Warehouse cannot change system state without an explicit human approval. Every action is audit-logged.
Relevant agents
The agents that work on this problem today.
Expected outcomes
What good looks like.
68%
Faster mean time-to-diagnosis
92%
Accuracy on held-out cases
3x
More issues resolved per shift lead
0
Unauthorised writes (policy-enforced)
Who this is for
Heads of warehouse operations, WMS practice leads, and supply chain transformation officers at mid-to-large enterprises running any modern WMS in production.
Let's talk about your operation.
Every engagement starts with a short, working conversation. No decks, no fluff.