BlindsWorth — AI-Powered E-Commerce Build

Shopify Development | AIGC Product Imagery | Solo End-to-End Execution

My Role:

End-to-end designer & developer · UX, UI, front-end, AIGC imagery, graphics

Team Members:

‍‍Solo project
(Independent Execution)

Duration:

‍‍2024
(3 months from concept to launch)

BlindsWorth is an independent Shopify-based e-commerce site that reimagines how traditional curtain and blinds manufacturers can go digital. Built entirely from scratch, the platform supports highly customized product configurations—dimensions, fabrics, blade sizes, and frame types—through a scalable, modular system.

To overcome high photography costs, I replaced traditional studio shoots with AI-generated product imagery, combining MidJourney and Photoshop to achieve photorealistic visuals indistinguishable from real photography. Together with custom Liquid logic and front-end scripting, the framework automated complex pricing and layout rules, cutting production expenses by over 95% while maintaining a premium brand presentation.

PROBLEM

High production costs and rigid templates made it hard for small brands to go digital.

PROCESS

From Costly Shoots to AIGC: How AI Saved 95% in Building My Store?

In early 2024, as AIGC rose to prominence, I adopted MidJourney, then the leading platform, to generate product imagery for BlindsWorth. Through progressively refined prompt-crafting and Photoshop post-processing, I pushed AI outputs to photorealistic quality, achieving results nearly indistinguishable from studio photography. Compared with today’s AIGC tools, MidJourney was still rudimentary — often requiring long, iterative prompt sessions — but even so, it replaced costly photoshoots with a faster, fully digital workflow that cut production costs by 95%.

The independent store was built from the ground up to support highly customized curtain and blinds products. Unlike standard storefronts, each item required complex logic for dimensions, fabrics, blade sizes, and frame types that varied by category. To meet this challenge, I extended Shopify’s native Liquid templating language, originally for basic dynamic rendering, into a more flexible architecture capable of handling category-specific configurations. With no prior Liquid experience, I used large language models to accelerate learning, generate code snippets, debug faster, and adapt templates for industry-specific workflows. The result was a tailored, scalable storefront that managed intricate options with ease and delivered a seamless shopping experience.

SOLUTION

Home Page

Collections

Steps

Products

Product Details & Configuration

Home Page

Collections

Steps

Products

Product Details & Configuration