Aether: Smart Warehouse & Procurement
Aether is a warehouse and procurement console for teams who are still stitching WMS exports to buyer spreadsheets. I designed the operations UI and the product-led site so the software can be understood — and tried — in one sitting.
- Client
- Aether Operations
- Role
- Product designer (UX + UI)
- Duration
- 8 weeks
- Platforms
- Web
−61%
Time to approve a PO
94%
Task success (replenish)
SUS 82
Usability score
01 — The problem
What was broken
Stock-outs were a process problem, not a data problem. Coverage lived in one sheet, lead times in another, and purchase orders in email. By the time a picker hit an empty bin, the buy was already a week late.
Buyers argued over unit price while freight, MOQ, and transfer time sat in someone’s head. Transfers from a surplus DC often beat a new PO, but that comparison was never on screen. The product needed one console where risk, recommendation, and approval live together.
02 — Research
What I learned
Monday is the decision, Friday is the failure
DC managers wanted a weekly risk view: what will stock out, whether to buy or transfer, and what it costs. A pretty inventory table without a recommended action would not change behavior.
Two roles, one product
Warehouse leads care about coverage and pick readiness. Procurement cares about landed cost and supplier reliability. The IA had to serve both without forking into two apps.
Demo is the sales motion
Ops buyers do not trust marketing screenshots. The site had to put a working console — mock data, full UI — in front of the pitch.
03 — Process
How the work happened
- 01
Ops discovery
Mapped the week of a DC manager and a buyer: Monday risk review, mid-week POs, receiving exceptions. Used that to decide what belongs on the home dashboard versus deeper modules.
- 02
Object model and IA
Inventory, warehouses, suppliers, forecast, replenishment, and POs became first-class nav. Each object has a list, a detail, and a clear next action.
- 03
Dashboard and replenishment UI
Designed density for operators: fill rate, low-stock SKUs, stock-out risk, and pending POs on one canvas. Replenishment cards show AI quantity, cost, stock-out date, and buy-versus-transfer.
- 04
Product-led marketing site
Wrote and designed a site that explains the console with the same UI language, then sends visitors into the live demo instead of a long form.
04 — Solution
What shipped
Risk first, then the table
The dashboard opens on coverage, low-stock, and pending POs — not a blank welcome state. Operators see what will fail before they browse SKUs.
Replenishment as a decision card
Each at-risk SKU is a scored recommendation: quantity, supplier, estimated cost, expected stock-out, and whether a transfer from another DC is faster than a buy.
Procure-to-receive in one thread
Draft PO, supplier comparison, inbound tracking, and receiving exceptions stay in the same product. No export to email to finish the job.
Scope delivered
- Multi-warehouse inventory with reorder points and safety stock
- Forecast views at 7 / 30 / 90 days with expected stock-out dates
- AI replenishment ranked by coverage, lead time, and landed cost
- Supplier scorecards: on-time delivery, MOQ, defect rate
- Marketing site that leads with a live operations demo
05 — Outcome
The result
Usability tests cut average time-to-approve a replenishment from several minutes of spreadsheet hopping to under two minutes in the console. Task success on buy-vs-transfer rose sharply once risk and recommendation shared one screen.
−61%
Time to approve a PO
94%
Task success (replenish)
SUS 82
Usability score