Abstract

This study looks at automating open-source intelligence (OSINT) activities to make data collection, analysis, and insight production more efficient. The core goal is to enhance intelligence gathering effectiveness across various fields such as business intelligence, law enforcement, and national security. Workflows for automating operations like data analysis, social media monitoring, web scraping, and alerting/notification systems are systematically designed and implemented. Iterative testing and refinement are applied to optimize performance, with prototypes developed to verify the efficacy of automated workflows. The study compares automated processes against manual strategies to evaluate the impact of automation on intelligence operations.