Core Insights - The project focuses on the development of an AI-based disaster recovery backup system that offers users a simple, cost-effective, and integrated recovery solution [1][3] - The system provides automated and intelligent data backup, recovery, monitoring, and management, ensuring business continuity in the event of data loss or disasters [1][2] Group 1: Technology and Innovation - The AI-driven disaster recovery system addresses traditional bandwidth costs and manual switching issues, utilizing AI technologies for unified management and on-demand bandwidth allocation, significantly reducing costs [3] - The project introduces a revolutionary breakthrough in data protection, innovating the business model by offering SaaS services that charge annual service fees, particularly benefiting small and medium-sized enterprises [3][4] Group 2: Cost Efficiency - The application of this technology effectively reduces data storage scale and controls the exponential growth of full backup data in archiving systems, leading to significant savings in data storage space and data center operational costs [4] - AI contributes to resource efficiency and cost savings, including reductions in data center power consumption, cooling costs, and physical space requirements, as well as decreased storage capacity, network bandwidth, and IT personnel needs [4][5] Group 3: Service Improvement - AI significantly enhances backup performance, allowing for completion within limited backup time windows, and improves recovery performance by leveraging random access disk storage compared to sequential access methods [5][6] - The economic viability of disk-based backups is improved for a wider range of applications due to the advancements brought by AI [6]