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Patent Mining for Engineers: Building an Agentic RAG System for Inventive Problem Solving using TRIZ & AI
Learn how to build an agentic RAG system that extracts TRIZ principles from patents to help engineers solve inventive problems with AI.
A pipeline that parses patent PDFs, extracts Technical Contradictions, classifies solutions into TRIZ Inventive Principles, and indexes everything into a vector database. This collection is then feeding an AI Agent that helps engineers solve real inventive problems.
The demo starts with a raw patent PDF, submits it live to the processing endpoint, and walks through what gets extracted and indexed. Then, given a real mechanical engineering problem, the agent frames it as a TRIZ contradiction, retrieves relevant patents, and proposes concrete solution ideas, powered by domain knowledge, not just plain LLM generation.