Case study · Marketplace operator (under NDA)
Generative Catalog Intelligence for a Marketplace
A generative enrichment pipeline turning inconsistent seller listings into structured, search-optimized product data — descriptions, attributes, and categorization at catalog scale.
Scroll
40x
Faster listing enrichment
95%+
Attribute accuracy (audited)
14 wk
Concept to production
Team — 5 specialistsDuration — 14 weeksIndustry — Ecommerce & RetailClient under NDA
The problem
Tens of thousands of seller-submitted listings with missing attributes and inconsistent descriptions suppressed search relevance and conversion. Manual curation couldn't keep pace with catalog growth.
What we built
The solution.
- 01Extraction and enrichment pipeline with per-category prompts and structured output validation.
- 02Human review queue for low-confidence items; automated approval above threshold.
- 03Continuous evaluation against a golden dataset with drift alerts.
- 04Warehouse integration feeding search, SEO pages, and merchandising.
OpenAI APIPythonFastAPIBigQuerydbtAirflow
Talk it through
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