Verified via pypistats.org — independent third-party statistics.
| Week of | Downloads |
|---|---|
| 2026-04-13 | ~2,896 |
| 2026-04-20 | ~2,607 |
Downloads are organic — no self-installs, no promotional campaigns.
enterprise-rag-patterns is a reference implementation library. Developers use it to:
- Enforce FERPA/HIPAA/GDPR at the retrieval layer — before any document reaches the LLM context window
- Audit all document access decisions — every retrieval produces a structured compliance record
- Adapt to any vector store — Pinecone, Weaviate, Qdrant, Chroma, OpenSearch all supported via adapters
50 sector-specific examples across every regulated industry:
| Sector | Regulations Enforced |
|---|---|
| Higher Education | FERPA (34 CFR § 99) |
| Healthcare / Hospital Systems | HIPAA, FDA 21 CFR Part 11 |
| Financial Services | GLBA, FINRA/SEC |
| Government / Public Sector | FedRAMP, FISMA, NIST SP 800-53 |
| Energy & Utilities | NERC CIP, FERC CEII |
| Insurance | NAIC Model Law |
| Legal / Law Firms | CCPA, attorney-client privilege |
| Defense / Aerospace | ITAR, EAR |
| Pharmaceuticals | FDA 21 CFR, GCP |
| Real Estate / Mortgage | RESPA, HMDA |
The standard enterprise RAG architecture applies compliance checks after the LLM processes documents. This is architecturally insufficient for FERPA, HIPAA, and GDPR:
- A post-processing filter cannot un-expose a document already in the context window
- FERPA defines a "disclosure" as any release of personally identifiable information — including to an LLM
- HIPAA's Minimum Necessary Rule applies at the point of access, not after processing
This library enforces compliance at the retrieval layer, before documents enter the context window.
- regulated-ai-governance — Policy enforcement for AI agent frameworks (CrewAI, AutoGen, LangChain, Google ADK)
- integration-automation-patterns — Enterprise integration and workflow orchestration patterns
- ferpa-haystack — Haystack-native FERPA document filter component