StowPilot
An AI warehouse slotting and pick-path platform that re-slots SKUs by velocity, plans pick waves, and routes pickers on the shortest path — cutting walk distance per pick.
// The Warehouse Control board — facility KPIs, a 12-week walk-distance trend falling from 114 ft to 88 ft, and a re-slotting queue ranked by walk saved.
Figures from the engagement, shared under NDA.
We publish them unchanged and can’t break them down any further here. The reference build you can open runs entirely on sample data.
If you read one part of this page, read these 4 lines.
- Cuts average walk distance per pick from 114 ft to 88 ft by re-slotting the building
- Turns velocity signals into ranked, one-click re-slotting moves for the ops lead
- Routes every wave on the shortest serpentine path across each picker's aisles
- Every move is explainable — feet saved, confidence, and the bin it picked and why
What it does — and which part of it we built.
StowPilot gives a third-party logistics operator an AI control room for the pick operation.
It ranks every SKU by velocity into A/B/C classes, re-slots fast movers into golden-zone forward pick, batches orders into balanced waves, and sequences each picker on the shortest serpentine route across their aisles. BuildspaceLabs designed and built the MVP front end — a Warehouse Control dashboard for facility-wide triage and a single re-slotting recommendation view that draws the before/after bin on a warehouse aisle grid — turning a slotting-optimization engine and a stream of pick history into moves an ops lead can approve in seconds.
Every screen here is from the reference build, not the client’s system.
The captions say what you are looking at. Every name and record on them is sample data.
What the engagement left the client with.
- Delivered a production-quality MVP of the Warehouse Control board and re-slot detail view in a 9-week engagement
- Consolidated slotting, wave planning, and pick routing into a single ops-lead workflow
- Cut modeled average walk distance per pick from 114 ft to 88 ft across the facility
- Established a reusable design system (velocity pills, aisle-grid map, confidence bars) for the product's next surfaces
The stack was picked per constraint, not per house habit.
7 technologies across 3 layers — the shape of the stack follows the problem.
Every feature in the build (6)
- Warehouse Control board with live orders-in-wave, pick rate, walk-per-pick, and slot-utilization KPIs
- Velocity re-slotting engine that ranks SKUs into A/B/C classes and suggests moves by walk saved
- Shortest-path pick routing that sequences each wave into a single serpentine per picker
- Wave planning that batches orders by zone and cart to stop aisle backtracking
- 12-week walk-distance-per-pick trend chart and facility slot-utilization tracking
- Re-slot detail with a warehouse aisle grid, projected savings, pick-frequency sparklines, and an explainable rationale
Don’t take our word for it — it is running in the frame below.
This is the same page the provenance block links to: our reference build for StowPilot, with its own look, copy and motion. Scroll inside it, or open it full-screen.
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