Each pack delivers structured, metadata-rich regulatory knowledge, pre-chunked and ready to drop into any vector database. From governance frameworks to healthcare guidance, your AI gets compliant in minutes.
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.
Anvil Index packs are built for the regulatory and compliance domains where getting the answer wrong has real consequences.
Only authoritative primary sources: legislation, official frameworks, and published guidance from NIST, the EU, FDA, SEC, Treasury, and other government bodies. Every source is publicly available.
Documents are split into atomic, self-contained units following the one thought per chunk principle. Each stays under 1,500 tokens to fit any embedding model.
Every chunk receives 17+ structured fields: jurisdiction, obligation type, source authority, AI lifecycle stage, and cross-references using controlled vocabularies.
SHA-256 checksums verify every file. Cross-references are validated. Controlled vocabularies enforced. Each pack ships with a machine-readable integrity manifest.
The foundational governance layer for AI compliance. Covers the EU AI Act, NIST AI Risk Management Framework and Playbook, three GPAI Codes of Practice (transparency, safety, copyright), and OECD's due diligence framework.
Maps the full AI threat landscape from vulnerability to defense. Covers OWASP's Top 10 for LLMs, MITRE ATLAS, CISA/NSA guidelines, and NIST's Cybersecurity Framework AI Profile, with a multi-framework crosswalk linking vulnerabilities to controls.
Covers the emerging patchwork of AI privacy regulation. Includes Colorado, Texas, and California state AI laws, the EDPB's joint opinion on AI and data protection, EU AI Act data governance provisions, and CISA's SBOM guidance.
The deepest available knowledge base for AI in financial services regulation. Covers SR 11-7, OCC MRM Handbook, Treasury AI frameworks, SEC exam priorities, GAO review, CFTC/PCAOB guidance, CFPB consumer protection, FinCEN deepfake advisory, and NYDFS cyber requirements.
Comprehensive coverage of AI in healthcare and medical device regulation. Spans FDA's AI/ML SaMD framework across four guidance documents, GMLP principles, EMA's reflection paper, HHS strategy, VA Trustworthy AI, AHRQ patient safety, CMS policy, and ONC certification requirements.
1,038 structured chunks from 44 authoritative sources. One unified schema, fully cross-referenced. Drop it into your vector database and go.
Six purpose-built AI agent skills that plug directly into your RAG Packs, turning static regulatory knowledge into active compliance workflows across every domain.
Automated compliance gap analysis against the EU AI Act, NIST RMF, and OECD frameworks. Map your AI systems to regulatory obligations and generate audit-ready reports.
Pairs with Pack 01Cross-reference OWASP, MITRE ATLAS, and NIST CSF controls against your AI system architecture. Identify coverage gaps and prioritize remediation by risk severity.
Pairs with Pack 02Evaluate AI data handling practices against Colorado, Texas, California, and EU requirements. Flag cross-border data transfer risks and generate compliance checklists.
Pairs with Pack 03Validate model risk management practices against SR 11-7, OCC guidance, SEC priorities, and Treasury frameworks. Reconcile audit findings with regulatory expectations across federal agencies.
Pairs with Pack 04Navigate FDA, EMA, and HHS requirements for AI-enabled medical devices and clinical decision support. Track submission pathways, predetermined change control plans, and patient safety guidance.
Pairs with Pack 05Track regulatory changes across all five domains. Get alerted when new guidance impacts your compliance posture and receive recommended updates to your knowledge base.
Pairs with All PacksWhen AI systems search for information, they work best when every piece of knowledge comes with clear labels describing what it is, where it came from, and what it relates to. That's what a schema does. Think of it as a standardized filing system: instead of dumping raw text into your AI, each chunk arrives pre-tagged with fields like jurisdiction, source authority, and obligation type. This means your AI can filter first, then search, giving you faster and more accurate results.
Every chunk traces back to a publicly available regulation, framework, or guidance document from government agencies and institutional bodies. No blog posts. No summaries of summaries.
Cryptographic checksums on every file. A machine-readable integrity manifest lets you confirm nothing has been altered.
Use in production applications, internal tools, and client-facing products. No attribution requirements. No copyleft restrictions.
Drop into Pinecone, Weaviate, ChromaDB, Qdrant, or any vector database. Standard .md and .json format needs zero conversion.
Semantic versioning tracks every change. When regulations evolve, updated packs drop into the same schema with zero rework.
See what you get and what you save.