Audience
EEnterprise IT, data, and business process teams wanting to automatically transform large volumes of unstructured content into structured, searchable, and actionable data to power workflows and analytics
About Box Extract
Box Extract is an AI-powered data extraction solution that intelligently identifies, retrieves, and converts structured information from unstructured content such as documents, spreadsheets, PDFs, images, and other file types into metadata that can be stored, searched, and used to automate business processes. It combines advanced large language models, integrated OCR, chain-of-thought prompting, extraction-specific retrieval-augmented generation, and agentic reasoning techniques to understand document meaning and structure with high accuracy, without requiring custom model training or heavy configuration. Users can choose between Standard and Enhanced Extract Agents, handling everything from basic fields like names, dates, and amounts to complex items such as risky clauses, tables, and graphs, and build Custom Extract Agents with configurable metadata templates that run at scale across folders and repositories.
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