Agentic AI For Autonomous Intellectual Property Breach and Brand Infringement Detection

Intellectual Property (IP) and brand assets are critical corporate value drivers, but their protection pose a rapidly expanding challenge in a data-saturated, high-speed world. Traditional methods of discovering IP infringements and brand violations remain manual, reactive, and helpless to act at scales necessary to facilitate proactive enforcement. We detail a new framework using an Agentic AI system to automatically monitor, detect, and classify suspicious IP infringements independently. The proposed multi-agent architecture merges internal IP knowledge bases supplemented by large-scale external sources, such as technology press, vendor guides, and social media streams. We outline an experiment focusing on center detection agent performance, measuring its ability to identify subtle IP violations by comparison against a ground-truth set labeled by legal experts. We compare multiple Generative AI models (Gemini 2.5 Pro, Gemini 2.5 Flash, GPT-4.1, GPT-4o, o4-mini) against a standard TF-IDF baseline. The results are very promising, where top-performing models achieved an F1-score of over 92%, demonstrating marginal gain in accuracy and efficiency compared to standard techniques. The AI-based approach transitions legal surveillance from a reactive to proactive mode, yielding fresh opportunities by unlocking IP commercialization, solidifying legal negotiation strength, and ensuring brand integrity.