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Enhanced Data Extraction using Gen AI

Enhanced Data Extraction using Gen AI

EY
Pages 16 Pages

This paper highlights how EY and Elastic apply generative AI to overcome challenges in extracting insights from unstructured, large-scale data. By integrating language embeddings, retrieval-augmented generation (RAG), and hybrid search strategies, their solution delivers superior accuracy, scalability, and speed compared to traditional pipelines. Case studies show efficient ESG and financial variable extraction, reducing errors, boosting performance, and enabling informed, sustainable decision-making.

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