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About this Project

🧾 Client Overview

A forward-thinking shoe manufacturing and retail brand approached Linea Digitech with a bold ambition: to transform the traditional e-commerce model into an AI-powered bid-and-ask marketplace, allowing customers to buy and sell shoes dynamically—similar to stock trading platforms.

To make this work, they needed AI-generated product listings that would automatically create accurate, engaging listings for every new shoe release, variation, and restock—reducing manual effort and boosting speed to market.


🎯 Challenge

The client wanted to disrupt their own direct-to-consumer and resale channels by creating a peer-to-peer dynamic pricing marketplace, but faced several challenges:

  • Manually listing thousands of shoe SKUs across sizes, styles, and colors was resource-intensive and error-prone
  • Traditional pricing models lacked real-time demand sensitivity
  • The client needed a system that was scalable, intuitive, and fully integrated with inventory, payments, and customer insights
  • The brand also wanted to offer personalized experiences to buyers and sellers while ensuring quality control

💡 Solution: AI-Driven Dynamic Shoe Marketplace with Bid-and-Ask Pricing

Linea Digitech designed and developed a full-featured AI-powered digital marketplace where customers could place bids to buy and asks to sell footwear, while the platform automatically generated listings using machine learning, handled intelligent matching, and provided real-time market signals.


🔑 Core Features Delivered

1. 💸 Bid-and-Ask Trading Engine

  • Customers place bids (buy offers) or asks (sell listings) on each shoe model and size
  • When a bid and ask match, the transaction is triggered automatically
  • Real-time trade dashboard shows current market activity and price history

2. 🧠 AI-Generated Product Listings

  • AI scrapes and parses internal product data (SKU, style, materials, colorways)
  • Generates:
    • Optimized product titles and descriptions
    • Style highlights and storytelling (e.g., “Built for the city streets with all-day comfort”)
    • Size availability, image tags, and fit notes
  • Reduces manual input by 90%, enabling instant go-to-market for new releases

3. 📸 Image Recognition for Sellers

  • Sellers can upload a photo of the shoe
  • AI identifies the model, matches it to a listing, and auto-fills details
  • Supports used and new condition grading with image-based quality estimation

4. 📊 Market Insights Engine

  • AI tracks and visualizes:
    • Bidding trends by region
    • Supply-demand gaps
    • Price volatility and value forecasts
  • Recommends ideal listing prices and bid amounts based on real-time data

5. 🛒 Inventory & Order Sync

  • Integrates with the brand’s inventory management system
  • Automatically updates stock status based on fulfilled orders and incoming seller listings

6. 📱 Buyer/Seller UX

  • Easy-to-use mobile-first interface
  • Smart notifications for price matches, drops, and trend alerts
  • Built-in wallet and escrow system for safe transactions

🛠️ Tech Stack

  • Frontend: React.js, Tailwind CSS, Next.js
  • Backend: Node.js, Express.js, WebSocket APIs for live price feeds
  • AI/ML: Python, spaCy, OpenCV, GPT-3.5 for content generation
  • Image Processing: TensorFlow Lite for on-device image classification
  • Database: PostgreSQL (relational), Redis (cache), ElasticSearch (search)
  • Hosting: AWS (EC2, Lambda, S3), Docker, CI/CD via GitHub Actions
  • Payments: Stripe and Razorpay with built-in escrow logic

📈 Results & Business Impact

Within 4 months of launch:

  • 📦 12,000+ product listings auto-generated by AI
  • ⏱️ Reduced manual cataloging workload by 90%
  • 📊 38% increase in sales velocity through bid-and-ask pricing
  • 📉 Reduced dead stock in slower-moving models by enabling customer-led pricing
  • 🔄 Repeat seller rate increased by 45%, thanks to simplicity and mobile-friendly listing experience
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