A browser userscript that consolidates three separate warehouse systems into one real-time dock-management view, then predicts which physical lane every package on an inbound trailer will land in, before unloading begins.
Recreation notice: this is an interactive recreation of an internal tool, rebuilt for this portfolio with entirely synthetic data. No proprietary systems, names, endpoints, or data are used or referenced.
Try it: load trailers → containers → packages, explore the tabs, then open Routing config and reassign a door range to a different sorter preset: the lane prediction re-runs live.
Dock managers planned inbound trailer placement by downloading and filtering Excel exports, a ~10-minute manual task that went stale the moment it finished. There was no way to know where a trailer's packages would physically accumulate until the trailer was already unloading, so lane congestion and door conflicts were discovered reactively, mid-shift.
Three internal systems each held a piece of the answer: one knew the trailers and their package volumes, one knew the facility's sorting equipment and lane topology, and one could report each package's routed destination chute. None of them talked to each other in a single view. The dashboard pulls all three together in the browser and runs a classification engine over the result:
package → routed chute → owning sorter → (preset overrides by size / container / door) → physical lane
The output is a per-trailer, per-lane forecast: which lanes will absorb how much volume, from which trailers, by when. Managers can rebalance doors, pre-stage labor at the right lanes, and spot bottlenecks while trailers are still in transit.
This recreation implements the actual classification algorithm on a seeded synthetic dataset (12 trailers, ~3,000 packages). The routing-config editor is live: change which sorter preset a door range uses and watch the lane distribution recompute: the same interaction managers use to plan door moves.