Beyond black boxes - building customisable and secure RAG systems for financial services

SurrealDB offers a unified data platform that addresses challenges faced by financial services in building retrieval-augmented generation (RAG) systems, which are often hampered by security concerns, lack of customization, and complex, fragmented data architectures. Unlike traditional RAG architectures that require multiple databases and APIs, SurrealDB integrates vector search, graph databases, document storage, and flexible relational queries within a single platform, enhancing data control, security, and analytical capabilities. This integration allows financial analysts to uncover hidden patterns and correlations in data, facilitating more insightful analysis and decision-making. SurrealDB's architecture supports real-time, interactive RAG applications by reducing latency and complexity, providing financial institutions with a customizable, secure, and efficient solution that meets regulatory requirements and enhances competitive advantage. The platform empowers users to experiment with different embedding models and language learning models (LLMs), facilitating prompt engineering and iterative development without the need for re-embedding data, ultimately enabling financial services to harness the full potential of their data and AI tools.