Architecture Overview
Welcome to the Kyoto NIST AI RMF Platform
The NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0 / NIST AI 100-1) is the industry standard for trustworthy and responsible AI systems.
Traditional compliance relies on annual spreadsheets and Word documents that quickly go stale. Kyoto AI RMF transforms compliance into an automated, code-native continuous integration engine with cryptographically verifiable evidence.
π‘ The 4 Functions: GOVERN (Policies & Risk Tolerance) β’ MAP (Context & Categorization) β’ MEASURE (Quantitative Testing & Verification) β’ MANAGE (Continuous Monitoring & Response).
Audited Target
The Audited System: examples/demo-rag-app
This live demo audits an enterprise Retrieval-Augmented Generation (RAG) knowledge assistant located at examples/demo-rag-app/:
- Application Service: FastAPI web server accepting domain knowledge queries
- Vector Database: FAISS with local sentence embeddings
- LLM Backbone: Google Gemini 1.5 Flash via Vertex AI API
- Risk Classification: MODERATE tier with human review loops
The Interview Wizard tailored the 72 AI RMF controls specifically for RAG hallucination, grounding, and sensitive document retrieval.
Automated Collectors
Zero-Trust Sandboxed Code Scanners
Kyoto AI RMF executes specialized automated technical collectors inside isolated Linux Bubblewrap sandboxes:
pip-audit (MAP 4.1): Scans Python dependency tree for known CVEs and malicious supply chain packages.
Fairlearn Probes (MEASURE 2.11): Computes demographic parity and equalized odds ratios across protected classes.
Garak & Promptfoo (MEASURE 2.7): Executes automated dynamic jailbreaks and hallucination evasion probes.
Fail-Closed Governance
Why Code Scanners Aren't Enough
A common compliance fallacy is assuming static analysis alone guarantees AI safety. NIST AI RMF is fundamentally a governance framework.
Even if all code tests pass, controls like GOVERN 1.1 (AI Governance Policies), GOVERN 2.2 (Executive Risk Tolerance), and MANAGE 2.4 (Decommissioning Plans) require designated human accountable owners.
βοΈ When an engineer or compliance lead signs off, the attestation is cryptographically hashed with Ed25519 and permanently committed to the ledger.
Auditor Deliverables
Machine-Readable Standards & Executive Briefs
With a single CLI command or button click, Kyoto compiles all evidence into certified enterprise deliverables:
- Executive Summary (HTML): Visual audit briefing with risk heatmaps and attestation matrices
- AI Nutrition Label: Public/customer-facing transparency disclosure card
- CycloneDX 1.6 ML-BOM: Standardized software and machine learning bill of materials
- NIST OSCAL 1.1: Machine-readable XML/JSON for enterprise GRC platforms (FedRAMP, Archer)
- Evidence ZIP: Complete cryptographically sealed archive with SHA-256 manifests