Store-agnostic Shopify taxonomy & category mapper
A backend pipeline that classifies any store's catalog against Shopify's Standard Product Taxonomy — rules first, AI where it helps, with human review and write-back.
First put to work on a live catalog of over 500,000 products.
What it does
Assigning every product to the right Shopify taxonomy category is tedious and error-prone by hand, and risky to fully automate. This pipeline does the heavy lifting while keeping a human in the loop for anything uncertain.
- Classifies products in two stages: fast, deterministic rules first, then Claude AI to re-classify only what the rules flag.
- Splits results into high-confidence (ready to write) and low-confidence (flagged for human review) — no silent writes.
- Writes approved classifications back to Shopify.
- Store-agnostic: per-client configs (store domain, custom rules, CSV input), so it runs for any catalog.
- Every run produces an auditable report — counts, review splits, and an AI cost estimate.
How it's built
- A Python pipeline built around a reusable engine package — the CLI is a thin wrapper, designed to drop into a service later.
- Two-stage classifier (deterministic rules + Claude AI) with dry-run and stage-by-stage execution modes.
- Per-client configuration and rules; Shopify Admin API for write-back.
- Built for scale and trust — catalogs from a hundred to 250k+ products, explicit review states, and validation before any write.