Case Study : AI-Powered Trademark Infringement Detection

 

Baianat’s trademark watch service relied on manual review to identify potential trademark infringement. As demand increased, the process became slow, resource-heavy, and difficult to scale while maintaining accuracy. The client needed an automated, reliable solution capable of handling a rapidly growing trademark portfolio.

 

 

Motqin.ai designed and developed an AI-powered image similarity detection system tailored for trademark monitoring. The system automatically analyzes trademark images, detects visual similarities across large datasets, and flags potential infringements in real time. The solution was built to integrate seamlessly with existing workflows while remaining scalable and accurate.

 

•Trademarks monitored: Increased from 100 → 2,400+

•Manual review time reduced: ~85%

•Detection speed: From days to near real-time alerts

•Operational efficiency improvement: 3x faster processing

•System accuracy: High-precision similarity detection with minimal false positives

 

 

The solution enabled Baianat to scale its watch service dramatically without increasing operational costs. Automated detection improved response times, reduced manual effort, and strengthened Baianat’s ability to deliver reliable, large-scale trademark monitoring.