1. The problem is to design an automated system that detects counterfeit products and verifies vendor authenticity using artificial intelligence. 2. This involves creating algorithms that analyze product and vendor data to identify patterns indicative of fraud. 3. Key AI techniques include machine learning classification, anomaly detection, and natural language processing for vendor reviews. 4. The system must be proactive, scalable, and capable of real-time analysis to prevent fraud before it affects consumers. 5. Implementing such a system requires collecting labeled data, training models, and continuously updating them to adapt to new fraud tactics. 6. The final solution improves efficiency by reducing manual checks and responding faster to counterfeit threats.