PQAI: Patent Quality Artificial Intelligence
Built production AI patent search platform processing millions of patents, serving 100+ daily users with ML-trained models from patent examination records.
Impact & Results
The Problem
Patent attorneys, researchers, and analysts spent hours manually searching through millions of patents for prior-art analysis, often missing relevant inventions due to complex patent language and keyword limitations. Traditional search tools couldn't understand conceptual similarity between inventions described in different technical terms.
The Solution
Developed PQAI, an AI-powered platform that takes plain language invention descriptions and finds similar prior work using machine learning models trained on past patent examination records. Built comprehensive ML pipeline with semantic search, patent classification, and intelligent ranking algorithms. Collaborated with AT&T to create enterprise-grade solution with API integration capabilities.
The Results
Successfully deployed production platform serving 100+ daily users including attorneys, researchers, and analysts. Helped 50+ enterprise clients analyze latest inventions and conduct prior-art searches. Achieved significant time savings in patent research workflows and improved accuracy of prior-art discovery. Open-sourced under MIT license with 108+ GitHub stars and active community contributions.
Technical Challenges
Training ML models on complex patent examination data, handling massive patent databases with millions of documents, building scalable architecture for real-time search, creating intuitive UI for complex patent analytics, ensuring accuracy for legal use cases, and maintaining performance under high concurrent usage from enterprise clients.
Screenshots & Gallery
