Financial Services AI Regulatory RAG Pack

Every time you ask an AI a question, you're giving it a test. If it doesn't know the answer, it might just make one up. RAG (Retrieval-Augmented Generation) fixes this by giving the AI an open book. It can look up real sources, reference them, and cite its work.

A RAG pack is that open book. A curated, structured collection of source documents, pre-processed and ready to hand to your AI. Instead of hoping the model remembers the EU AI Act or the FDA's guidance on medical device software, you give it the actual text, organized so it can find exactly what it needs.

208 chunks from 12 sources across US banking regulators, securities examiners, consumer protection agencies, and international standard-setters. Sources include SR 11-7, OCC MRM, Treasury AI Report, GAO, SEC FY2026 Priorities, CFTC, PCAOB, CFPB, FinCEN, NYDFS, IOSCO, and the CRI FS AI Risk Management Framework.

Seven controlled vocabularies covering regulatory_domain, financial_sector, ai_lifecycle_stage, obligation_type, affected_entity, jurisdiction, and document_type. Cross-references to Governance, Security, and Privacy packs.

Built for model risk management, exam preparation, fair lending compliance, and financial crime detection. All sources US public domain or permissively licensed. Commercial license included.