Shopify · Supplier CSV
Her-age CSV_CMD — supplier dumps in, a quality gate, taxonomies out. The UI is theirs. The pipe is ours.
CSV_CMD is Her-age's internal tool: take supplier CSV from Shopify and from custom CMS / ERP, normalize, run an AI quality filter, apply taxonomies for import or export. Client designed the UI — we say so. Fastify on the back, Next.js dashboard, Remix + Polaris as the embedded Shopify app. File converter, auto-updater, pattern matcher, AI analyzer, CSV editor, taxonomies. Integration speed +56%. Fully automatic. Uptime over a year without intervention.
- integration speed
- +56%
- end to end
- Auto
- no intervention
- >1 yr
Many sources, one gate
Suppliers do not arrive in one shape. Shopify exports, custom CMS, ERP dumps. CSV_CMD ingests them, normalizes the rows, then a quality filter: no photo, three or more empty critical fields, duplicates, price and size anomalies. What survives gets a taxonomy — for import into the store or for export out.
Their screens, our pipe
The UI was designed by Her-age. We built the engine. Fastify backend. Next.js dashboard. Remix + Polaris for the embedded Shopify app. AWS and DigitalOcean, cron on the clock. GPT-2 sits in the listed stack as the AI analyzer — we do not invent model scores on top of that.
- File converter
- Auto-updater
- Pattern matcher
- AI analyzer (quality gate)
- CSV editor
- Taxonomies for import and export
The third Her-age product
Not the store redesign. Not Sell with Us. Not NFTIZE. CSV_CMD is the supplier integration tool that kept running. +56% faster to integrate. Automatic. More than a year up without someone in the seat.
Technologies
- Fastify
- Shopify
- Remix.js
- Next.js
- GPT-2
Outcomes
- +56% integration speed versus the previous supplier path
- Fully automatic ingest → filter → taxonomy → import or export
- Uptime over a year without intervention
Recommended articles
Blog
The case for boring web stacks
TypeScript, Postgres and edge deployment are not exciting — they are how you still iterate fast in year three without rewriting the platform.
Blog
Shipping evals before prompts
Why we run regression suites on LLM outputs before every release — and how it changed our AI delivery cadence at ZNN.
Blog
Mobile release trains that do not break
Fastlane, staged rollouts and feature flags — a practical playbook from eighteen App Store submissions without a Friday-night rollback.
Recommended case studies
Luxury · Volume eDTL
The Brand Collector
The Brand Collector resells pre-owned luxury through a supplier network. Same class of problem as a catalogue feed — except each dump crossed 120,000 rows, and the CSV they hold sits above 169,000. Fastify stayed the orchestrator. The heavy compute moved to Go workers. About 60% faster on taxonomy, mapping and pattern-match at that volume.
iGaming · Platform
Casino operator · NDA
Under NDA we stabilised three production gambling brands: cleaned up legacy PHP/JS stacks, extracted shared modules, and shipped a new marketing site without stopping live traffic.
Marketing · Fintech
Digital DAO
Digital DAO is a marketing studio in Belarus that works mostly with fintech. We did not repaint the old site. We rebuilt the story and the visual system so it would sit in a room with banks, not with a carnival agency deck.