Logistics Ops Dashboard

The brief we build from

This is the exact instruction PromptUI starts with. You can change every word of it before or after the first build.

Build Parcelane, an operations control tower for our fulfillment and last-mile delivery network. I run dispatch and I want a single dense screen — no side navigation, everything reachable from a top filter bar.

Across the top put a row of KPI cards: total shipments in range, on-time rate, average transit time, open exceptions, and delivered count — each with a small up/down delta versus the prior period.

The hero of the page is a dense shipments table. Columns for tracking number, route (origin → destination), region, service level, a colored status chip, package count, an ETA / delivered cell that reads "in 3 hours" or "6 hours late", and when it was last updated. Every column header must actually sort, ascending/descending, and clicking a row should expand it in place to show the full tracking-history timeline (pickup scan, hub sortation, out for delivery, delivered), the customer, load weight, assigned driver and vehicle, and — if something went wrong — the exception detail with a "mark resolved" button. Each row also needs a little actions menu (notify customer, add a note, resolve).

On the right, a regional breakdown bar chart showing shipment volume per region; clicking a bar should filter the table to that region. Under it, an exceptions queue that lists everything currently delayed or in exception with a severity tag and a resolve button, so my team can work the problems top-down.

Filters live in the top bar: date-range chips (Today, 7 days, 30 days, Quarter), status filter chips with live counts, a region dropdown, and a search box for tracking numbers, customers, or cities. Show how many shipments match and a clear-filters link.

Design it like a calm operator cockpit: a warm stone/gray paper background, cool slate data ink, one deep-orange accent for anything live or actionable, and a fixed set of status colors. Data-dense but never noisy, tabular numerals so the columns line up, and the table clearly the center of gravity. Use realistic logistics data — real-sounding cities, routes, tracking IDs, carriers, and believable exceptions like weather holds and missed connections.

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