Automated Counterfeit Detection and Reporting System
Budget: $250 – $750 USD
I need a robust system to combat counterfeit products and sellers on e-commerce platforms like Amazon and Alibaba. The project involves integrating an e-commerce scraper API with a large language model (LLM) like GPT or Gemini to detect fraudulent activities.
Key Components:
- Data Scraping: Gather product details, seller info, and customer reviews.
- Detection Mechanism: Employ a method (not limited to ML or rule-based) to identify counterfeits by integrating with LLM
- Takedown Engine: Automate reporting and removal of counterfeit listings.
- Technology Stack: Frontend in React, Backend in Python. I have some basic backend code and UI screens ready.
- Testing: Evaluate various e-commerce platforms and data sources for optimal performance.
Ideal Skills:
- Experience with APIs and data scraping
- Proficiency in Python and React
- Familiarity with LLMs and fraud detection methods
- Background in automation and integration with e-commerce platforms
Looking for a candidate who can efficiently build the data layer, detection layer, and takedown engine.
Key Components:
- Data Scraping: Gather product details, seller info, and customer reviews.
- Detection Mechanism: Employ a method (not limited to ML or rule-based) to identify counterfeits by integrating with LLM
- Takedown Engine: Automate reporting and removal of counterfeit listings.
- Technology Stack: Frontend in React, Backend in Python. I have some basic backend code and UI screens ready.
- Testing: Evaluate various e-commerce platforms and data sources for optimal performance.
Ideal Skills:
- Experience with APIs and data scraping
- Proficiency in Python and React
- Familiarity with LLMs and fraud detection methods
- Background in automation and integration with e-commerce platforms
Looking for a candidate who can efficiently build the data layer, detection layer, and takedown engine.