Beyond RAG: Using YugabyteDB as the Foundation for Reliable AI Decisions

YugabyteDB is positioned as a foundational database solution that supports reliable AI-based loan decision-making in India by ensuring compliance with regulatory requirements such as those from the Reserve Bank of India. It combines transactional consistency, distributed scalability, and PostgreSQL compatibility to store customer data, policy checks, AI recommendations, and audit logs in a unified data layer. This setup facilitates fast, explainable, and reproducible decisions by integrating Retrieval Augmented Generation (RAG), Cache Augmented Generation (CAG), and a high-throughput LLM serving framework (vLLM). The architecture enables efficient vector searches for past decisions, maintains a static policy context, and leverages GPU memory for optimized inference, ensuring that all components remain synchronized and traceable. The design is modular, allowing for future enhancements, and serves as a reference architecture for deploying AI applications that require a single source of truth and auditability, exemplified by its ability to process and log underwriting decisions seamlessly.