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A five-stage evolution of AI-powered clinical data extraction is traced from 2019 to present, covering SpaCy-based NER, early LLM adoption, LangChain/Kor orchestration, RAG, and multi-agent systems. Each stage includes architecture details, performance metrics, and lessons learned. The current multi-agent platform achieves 90%+ accuracy at 15–20 docs/min with 90% reduction in annotation effort, parsing text, tables, and figures from clinical trial publications for pharmaceutical research.