Curious how other resellers decide which liquidation lots are even worth deeper research. For me, the biggest time sink has always been reading messy manifests and trying to ballpark resale value and risk before bidding. I m interested in what signals make you instantly skip a lot versus dig in further, and whether you rely more on gut, past data, or tools to narrow things down.
I tend to build products by starting with the problem and then iterating on the design until it feels obvious.
LotFilter came from spending way too much time clicking through liquidation marketplaces, reading messy manifests, and trying to mentally estimate whether a lot was even worth deeper research. Most of the work happens before bidding; comparing lots, estimating resale value, and spotting risk; but that part is almost entirely manual today.
So I focused on building something that sits one step earlier in the process: aggregating lots across marketplaces and analyzing manifests to help narroww down which auctions are actually worth investigating.
This is still very much a work in progress, and I m genuinely curious how others approach this problem. A few questions I d love feedback on:
LotFilter aggregates wholesale liquidation lots from multiple marketplaces and analyzes their manifests using AI. It estimates resale value, fees, and risk so resellers can quickly identify which lots are worth deeper research before bidding.
