Automação de triagem e classificação de documentos em contencioso de massa e eDiscovery

uma abordagem integrada da tecnologia de Processamento de Linguagem Natural

Abstract

This article examines how Natural Language Processing (NLP) techniques and machine learning models transform the screening and classification of legal documents in mass litigation and electronic discovery (e-discovery) contexts. Analyses indicate that AI-powered tools can significantly reduce the time required for document review, improve the accuracy of categorization, and identify patterns in large volumes of legal data. This study synthesizes the underlying technologies, their practical applications in the legal sector, and the challenges associated with the responsible deployment of these solutions, structuring an analysis that begins with general NLP technologies and proceeds to specific implementations in mass-litigation environments.