The team started by collapsing fragmentation. Fifteen-plus data sources — mainframes, Bloomberg, credit bureaus, CRM — were consolidated behind a real-time API layer on Kafka and Snowflake, giving every downstream agent one clean feed instead of fifteen interfaces. On top of that mesh they ran a swarm of specialized agents: rather than process a borrower sequentially, separate agents handled data extraction, financial analysis, regulatory checks, and report generation in parallel. A proprietary ML scoring engine, trained on a decade of credit history, produced risk grades that stayed fully explainable to regulators — a hard requirement in a Basel III/IV environment. Compliance itself was automated: stress tests and audit trails generated on every assessment, removing the manual reporting burden. Delivery was principal-led and production-first — senior engineers on the keyboard from week one, every artefact shipped behind a load balancer, and scope locked to the P&L metric at kickoff. The full build reached production in sixteen weeks.