The context
Returns are a margin sink. Inbound classification is manual, disposition (resell, refurbish, recycle, scrap) is rule-of-thumb, and reverse-logistics routing is solved at the warehouse level with no view of the network.
Why it doesn't scale today
Most return management software focuses on the customer side — the RMA, the refund. The operations side, where the margin recovery actually lives, has been undertooled. Generic AI has the wrong sense of value: it optimises the wrong things.
What we ask in week one
- iFor each of your product families, what is the actual margin recovery by disposition path today?
- iiWhere can vision and document AI classify your inbound returns at line speed?
- iiiHow do we route disposition against your live resale-channel demand and your current refurb capacity?
- ivWhat does the override surface look like for your warehouse team — the people who'll catch the misclassifications?
What we build
Inbound classification by vision and document AI, dispositioning routed against live resale-channel demand and refurb capacity, reverse-logistics optimisation against the actual network. The warehouse team owns the override; the system improves recovery without taking decisions away.
Why we're the right squad
We have shipped returns operations for retailers and specialty CPG firms. The math behind disposition value is unforgiving — and we have done it before.