Regulated AI Starter Kit

A GitHub template repository giving AI teams a running start on governance documentation, release-readiness artifacts, and deployment-readiness structure for regulated or high-accountability environments.

Click Use this template above to create your own copy pre-wired with:

NIST AI RMF-informed governance documentation
release readiness configuration stubs
a structured risk taxonomy with practitioner mappings to NIST AI RMF and EU AI Act concepts
CI/CD validation workflows
incident response playbook stubs
model card templates
generic sample artifacts that show how to fill the templates safely

This repository is a starter kit. It is not legal advice, compliance certification, regulatory approval, safety certification, or a substitute for formal safety, privacy, legal, security, or regulatory review.

Maturity

This is a template repo. It is intended to help teams start with better structure, not to certify that an AI system is safe, compliant, production-ready, or approved for release.

Who this is for

Teams deploying AI in:

Healthcare for clinical decision support, diagnostic AI, or patient risk scoring
Financial Services for credit scoring, fraud detection, or model-assisted decisions
Insurance for underwriting AI, claims automation, or risk assessment
Government for benefits eligibility, document processing, or public-facing AI
other high-accountability domains where governance, traceability, and release discipline matter

Repository structure

regulated-ai/
├── docs/
│   └── how-to-use-this-template.md
├── examples/
│   ├── sample-release-checklist.yaml
│   └── sample-risk-register.md
├── governance/
│   ├── ai-governance-policy.md
│   ├── roles-and-responsibilities.md
│   ├── model-inventory.md
│   └── nist-rmf-mapping.md
├── risk/
│   ├── risk-register.md
│   ├── risk-taxonomy.yaml
│   └── risk-assessment-template.md
├── release/
│   ├── release-checklist.yaml
│   ├── release-readiness-report.md
│   └── deployment-approval.md
├── incident/
│   ├── incident-response-playbook.md
│   ├── incident-report-template.md
│   └── escalation-matrix.md
├── model-cards/
│   └── model-card-template.md
└── .github/
    └── workflows/
        ├── validate-release-config.yml
        └── governance-checks.yml

Quick start

1. Create your repository from this template

Click Use this template and create a new repository such as acme-ai-governance or {team}-ai-deployment-kit.

2. Follow the adoption guide

Start with docs/how-to-use-this-template.md. It explains what to edit in the first hour and first week after creating your copy.

3. Customize the governance policy

Edit governance/ai-governance-policy.md and replace [Organization Name] placeholders with your organization name, decision rights, and internal approval path.

4. Configure your release checklist

Edit release/release-checklist.yaml to reflect your actual controls, owners, and risk tier. See examples/sample-release-checklist.yaml for a generic filled example.

metadata:
  project: "Your Project Name"
  version: "1.0.0"
  environment: "production"
  regulated_industry: "healthcare"
  risk_classification: "high"

model_validation:
  performance:
    accuracy_threshold: 0.95
    bias_evaluation_complete: true

governance:
  documentation:
    risk_assessment_complete: true
  approvals:
    technical_review: true
    legal_review: true

infrastructure:
  testing:
    unit_tests_passing: true
  rollback:
    rollback_plan_documented: true

5. Run the CI validation

Push to any branch to trigger the included GitHub Actions checks.

git add .
git commit -m "Configure regulated AI starter kit"
git push

6. Complete your risk assessment

Copy risk/risk-assessment-template.md and fill it out for each AI system you are deploying. Use examples/sample-risk-register.md as a simple reference for owner, mitigation, and status discipline.

NIST AI RMF mapping

This starter kit is organized around the four core NIST AI RMF functions:

Function	Implementation in this kit
Govern	`governance/` directory for policy, roles, and model inventory
Map	`risk/` directory for taxonomy and per-system assessments
Measure	`release/` directory for pre-deployment checks and readiness artifacts
Manage	`incident/` directory for monitoring, escalation, and response

This is a practitioner mapping, not an official NIST assessment or endorsement.

Public-safe example rule

The examples in this repository are intentionally generic. If you use this template in a public or shared repository, do not include customer data, employee data, confidential vendor details, unreleased product names, proprietary model results, internal approval chains, sensitive logs, or real incident details.

Scope and disclaimer

This repository is shared in a personal capacity. It is not legal advice, compliance certification, regulatory approval, safety certification, or official guidance from NIST, the EU, ISO, or any employer.

References to NIST AI RMF, EU AI Act, release readiness, risk taxonomy, model cards, incident response, or regulated-industry obligations are practitioner mappings and examples. Always verify against official sources and internal requirements before using this template for compliance, safety, or release decisions.

Repository	What it adds
governance-playbook	Full governance playbook with broader operating-model guidance
release-checklist	CLI validator and stricter release gate logic
release-governance	Release lifecycle governance framework
nist-rmf-guide	Practitioner guide for implementing NIST AI RMF
ai-prism	Curated list of governance tools, frameworks, and references

License

MIT License. See LICENSE.

Maintained by Sima Bagheri · Built for AI teams working in regulated and high-accountability environments.