As someone who frequently spins up online services and infrastructure for new MVPs and prototypes, I often lose track of recurring expenses tied to abandoned or paused projects. These small leaks can quietly drain resources over time. To solve this, I developed a local AI-based data analytics framework that aggregates exported transaction logs from all my financial institutions. The system standardizes formats, harmonizes categorization and codes, and merges everything into a unified dataset for monthly review. Once consolidated, I can easily sort purchases by amount and identify recurring charges or subscriptions that no longer serve a purpose. This empowers me to proactively plug financial leaks and improve spending efficiency. The entire system runs securely on my personal machine—no cloud processing involved. It automatically cleans, merges, categorizes, and updates transaction data with no manual effort. Over time, this tool has saved me dozens—if not hundreds—of hours while safeguarding my finances with precision and privacy.