Textile Mill Quality AI — Surat

The Challenge

Manual inspection of high-speed looms led to a 12% defect pass-through rate, resulting in rejected bulk export orders and massive financial losses.

The Solution

Implemented a Computer Vision model mounted above the looms that instantly identifies threading errors and alerts operators via a localized Gujarati dashboard.

Key Outcomes

Technical Specification

/* Recommended Tech Stack */
Python + Computer Vision + React + Node.js

/* Architecture Overview */
1. Connect to Python for the frontend core.
2. Integrate Node.js for production-grade API handling.
3. Use Zynteq-optimized prompts for higher accuracy.

/* Deployment Target */
- Vercel for Frontend
- Supabase for Database/Auth