Contact person: AI Fraud Detection DApp Module

Phone:Show

Email:Show

Location: Osaka, China

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Task Title: AI Anti-Fraud Module Development Task Description:
We are developing a community management DApp. This task involves independently developing an AI anti-fraud module to detect and filter fraudulent content or data within user-submitted information, enhancing platform trustworthiness. Requirements: Utilize Hugging Face NLP models to analyze user-submitted inputs (e.g., group names, descriptions, or feedback) and flag suspicious content.
Develop backend logic in Python, creating API endpoints (e.g., POST data, return filtered results).
Integrate with MongoDB to store flagged data, ensuring a response time of less than 2 seconds and 90% accuracy based on 200 test cases.
Ensure the module is independent and compatible with existing systems, without requiring access to external group ecosystems.
Deliver via a private GitHub repository (link provided after hire, use feature branches, and submit pull requests daily).
Budget: $300-450" (client-provided description)