​W​e conducted a comprehensive strategic and technical audit designed to transition the Quorum Platform from a brittle, manual system into a scalable, ML-ready architecture. The nature of the work ​w​as dual-faceted, focusing on immediate operational recovery​ (such as identifying over $60,000 in annual infrastructure savings through Snowflake storage optimization and AWS right-sizing​) while simultaneously architecting a long-term technical foundation. This include​d the design of a five-layer medallion data architecture to reduce schema complexity by 90%, the replacement of fragile EC2 orchestration with cloud-native workflows, and the creation of an output adapter framework to accelerate client delivery speeds by fivefold. The scope of this consulting effort extend​e​d beyond infrastructure into product-level data science and organizational design. ​O​ur Engineering Manager defined a rigorous roadmap for improving attribution accuracy through ML-optimized windows and the implementation of a feature store and semantic layer to enable future LLM and AI capabilities. To ensure these recommendations ​w​ere actionable, the work conclude​d with a detailed ​s​taffing plan, specifying the team structure, hiring timelines, and technical competencies required to execute the transformation over a 120-day period. Ultimately, the manager has provided a total lifecycle blueprint that addresses technical debt, financial waste, and product innovation to position the company for sustainable growth.