Multi-source research
Cross-references OEM sites, eBay, Amazon and other spec sources for each part.
Service · AI Product Data & Marketplace Automation
AI product data and marketplace automation.
Built-N-AI builds AI tools that research, validate and fill in missing product attributes across an entire catalog, score every field for confidence, and push updates to marketplace listings automatically — then keep running on every new part.
The problem
Thin product records cost you sales and never get fixed by hand.
In the attribute backfill case study, parts existed in the ERP with only 4–5 attributes each. Researching the rest by hand took about 5 minutes per part number — a backlog no team was ever staffed to attempt.
Incomplete records produce thinner marketplace listings, which affects impressions, conversion and sell-through.
What we build
Research, validate, score, sync.
Validation and dedupe
Compares embeddings of spec data to find and merge the closest match across sources.
Confidence per field
Every field returns with a confidence score on a review dashboard.
Same-day marketplace sync
Updates push to every marketplace listing automatically, and the tool keeps running on new parts.
Proven results
Real numbers from prior operating work.
300,000Parts backfilledFull database in 9 days
98%AccuracyAfter about a week of tuning; no manual check required
$625,000Equivalent labor avoided25,000 hours at $25/hour
OngoingAutomatic for new partsPart creation through listing update
How engagements start
Call, assess, then prove it on your data.
Every engagement starts with a free 30-minute call. If there is nothing worth your money, we will say so.
The next step is a flat-fee assessment ($1,500–$2,500 based on company size): a written report in one to two weeks that ranks opportunities by value against effort — including the ones where AI is the wrong tool.
Proven workflows can start with a short pilot on your own data before you commit to a full build. Founding-client pilot pricing is listed on each case study.
Start with a conversation
What problem is costing you more than it should?
Let’s spend 30 minutes looking for the first problem worth solving.