Rufous & Co: An AI Image Pipeline Across a 759-Product Catalog
Rufous & Co: An AI Image Pipeline Across a 759-Product Catalog
Services:
Web Design & Development
Industry:
Interior design & home retail (Seattle)
Timeline
May 2026 to June 2026
Snapshot
759 — products in catalog
222 — products scoped for AI image regeneration
~111-222 hrs — manual editing replaced (est.)
The challenge
A Seattle interior-design studio and Capitol Hill home boutique needed its online funnel to sell the higher-value interior-design service, not just decor. The catalog was large and the product imagery was inconsistent.
What I did
Rebuild all five pages on Shopify and reposition the brand from home-decor shop to interior-design studio, then build a reusable pipeline to fix catalog imagery at scale rather than editing photos by hand.
The work
A custom Astra-schema theme with custom Liquid sections: a cinematic hero, a tabbed Design Services explorer, an editorial Store with 20+ curated category cards, a qualifying Contact form, and a Portfolio with a before/after slider carrying 108 photos renamed for local SEO across 11 Seattle projects. Then a Python image-regen pipeline emitting three variants per product — 666 target images across 222 products.
Stack: Shopify, Liquid, custom Astra-schema theme, Figma, Python, Google Flow, Nano Banana Pro, Shopify Dev MCP
Catalog: 759 products, 222 scoped for AI regeneration across 7 categories (666 target images)
Latest batch: 60 successful regenerations across 28 products from 106 attempts
Portfolio: 108 photos renamed with local-SEO filenames across 11 Seattle projects
Efficiency: ~111 to 222 hours of manual editing replaced (est.)
A pipeline beats a retouching queue. The value was not the images, it was never having to do them by hand again.
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