AI Governance 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.

339 production-ready chunks from 8 authoritative sources including the EU AI Act, NIST AI RMF, NIST AI 600-1, GPAI Codes of Practice, and OECD Due Diligence Guidance. Every chunk stays under 1,500 tokens with 17 structured metadata fields covering jurisdiction, obligation type, AI lifecycle stage, and cross-references.

Built for compliance chatbots, regulatory Q&A agents, governance gap analysis tools, and policy monitoring pipelines. Compatible with Pinecone, Weaviate, ChromaDB, Qdrant, and any embedding pipeline that accepts JSON.

Ships with INDEX.md, pack_metadata.json, CHECKSUMS.sha256, pack_integrity.json, CHANGELOG.md, and organized chunk directories. Commercial license included.