The primary accomplishment of this milestone is the significant enhancement of FluereFlow's live extraction feature, which now boasts greater stability. However, there's room for improvement: the codebase still requires more modularization and expanded Lua-based customization options. To achieve full-scale stability and functionality, the system needs to be enriched with a broader range of capabilities, akin to those offered by Zeek, and should include an optional GUI reminiscent of Sniffnet. A crucial aspect of this enhancement is the advanced integration of the system with Python, specifically designed to bolster AI-powered security applications.

Initially developed for research, the project is now pivoting to meet the needs of enterprises. Future upgrades are aimed at enabling effective monitoring of both on-premises environments and cloud infrastructures, including platforms such as AWS and Oracle. Balancing its research origins with practical enterprise applications, the software is evolving into a versatile tool for both academic research and professional use. A key focus of these enhancements is to position the tool as an essential data provider for AI-driven security applications, ensuring robust security enhancements and cost-efficiency, all while upholding strict privacy standards.