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Explore advanced techniques for performing semantic analytics on unstructured data at scale using the Aryn AI-powered data warehouse system. Learn how recent improvements in generative AI model efficiency (50-80x cheaper, 10-20x faster) enable complex analytical workflows beyond traditional RAG approaches. Discover how to analyze thousands of documents for insights in pharmaceutical marketing research and financial due diligence through natural language queries that automatically generate and execute semantic plans. Examine the system architecture that orchestrates visual AI models and LLMs using the open source Sycamore library, with practical demonstrations using real-world National Transportation Safety Board (NTSB) reports. Understand the end-to-end process of data ingestion and indexing with Sycamore and OpenSearch, query planning and execution for superior accuracy compared to RAG methods, and the importance of verifiable analytics systems with explainability features including lineage tracking and execution traces to build user trust.
