Case Study
AI Fashion Platform
Modelia · 2024 — 2025
SSR/CSR hybrid AI platform serving 100k+ users with real-time image generation workflows.
ReactTypeScriptNode.jsAI/MLSystem Design
Problem Statement
The platform needed to support compute-heavy AI image generation while maintaining a responsive UX at 100k+ user scale. High latency risk and unpredictable backend load required a robust frontend architecture.
Hybrid SSR/CSR with Async Job Queue
I worked on a hybrid ssr/csr with async job queue where:
- SSR for initial shell + SEO-critical paths
- CSR for interactive AI studio workflows
- Node.js API layer for request orchestration
- Async queue decoupling AI jobs from user requests
- CDN-backed asset delivery for generated media
Frontend (React SSR/CSR)
→API Layer (Node.js)
→AI Processing Queue
→Model Execution Layer
→Storage / CDN
My Contributions
- Architected hybrid SSR/CSR system optimized for AI workloads
- Built Node.js backend APIs for AI workflow orchestration
- Integrated generative pipeline with real-time UI feedback
- Built 20+ reusable component library reducing delivery time by 25%
- Collaborated with UX/product on Figma handoffs and design tokens
Engineering Trade-offs
- Chose SSR for initial loads over full SPA simplicity
- Accepted eventual consistency via async jobs to keep UI responsive
- Balanced cache TTL to keep generated assets fresh without CDN storms
Impact
100k+
active monthly users
30%
response latency decrease
25%
faster feature delivery via component reuse
15%
reduction in UI defect escape rate