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Making Messy Business Documents Trustworthy: The Case for Review-First Data Extraction
비즈니스 문서를 신뢰할 수 있는 데이터로: 자동화와 검증의 올바른 균형
Why it matters
Most business document cleanup fails because pure automation doesn't ensure data quality—it requires explicit validation and review. This article presents a proven workflow pattern where saved 'recipes' (output schemas, extraction rules, and review notes) enable teams to reliably convert messy PDFs, emails, and screenshots into trusted spreadsheets, showing why lightweight specialized tools beat generic document converters.
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Document extractionData validationBusiness automationMessy2SheetReusable recipes