Looking for contributors: AI compliance policies, examples, and integrations

[kmadan]

AICertify is open-source compliance-as-code for AI systems. We're looking for help from the AI engineering, governance, OPA, and Python communities.

This is the pinned umbrella issue. Individual starter tasks live in good first issue and help wanted. Comment here if you'd like a recommendation for where to start.

Where help is most welcome

📚 Documentation and onboarding

• Better quickstarts (web app, notebook, Docker)
• Tutorials covering a single compliance flow end-to-end
• Translations for the four existing locales (zh-CN, ja-JP, ko-KR, hi-IN) as features evolve

📦 Application examples

We ship three forkable examples (customer-support-bot/, healthcare-triage-bot/, hiring-screening-bot/) and want more:

• LLM-framework integrations (LangChain, LlamaIndex, agent frameworks)
• Industry-specific examples (financial-advice, edtech-tutor, internal-hr, RAG-knowledge)
• Deployment-shape examples (FastAPI service, batch job, GitHub Action)

🛡️ Policy and framework coverage

The policy library is gopal. Help is welcome on:

• New regulatory frameworks (UK AI principles, California SB-1047 successor, MAS / HKMA AI guidance, Australian Voluntary AI Safety Standard, Brazil PL 2338 once enacted)
• Industry verticals (insurance, defense, hiring as its own framework, RAG-specific)
• Operational policies (incident response, model-card requirements, CI gate policies)
• Test coverage on existing policies
• Improvements to the helper functions (reporting.rego, validation.rego)

🧪 Evaluators and integrations

• Better bias evaluators
• Hallucination evaluators for RAG
• Tool-use safety evaluators for agent frameworks
• Adapters for popular logging frameworks (LangSmith, Phoenix, MLflow)

🛠️ Developer experience

• One-line installers (`uvx aicertify ...`)
• A first-class `aicertify init` command
• An MCP server so Claude Code / Cursor users get policy checks as native slash commands
• Pre-commit hooks for evaluation

Who should contribute?

You do not need to be an AI governance expert. Useful contributions come from:

• AI engineers who can describe what their compliance pain looks like
• GRC / audit / model-risk professionals who can sanity-check whether a policy actually maps to the regulation
• OPA / Rego users who can author or improve policies
• Python developers who can ship integrations, examples, and tooling
• Tech writers who can turn dense docs into onboarding ramps

Non-code contributions (examples, policy mappings, docs, tests, report templates, regulatory notes) are very welcome.

How to get started

1. Pick an issue with the good first issue label.
2. Comment "I'll take this" and any clarifying questions.
3. Open a draft PR as soon as you have a skeleton — early feedback beats finished surprises.
4. Read CONTRIBUTING.md, the Code of Conduct, and the Security Policy.

If you're not sure where to fit in, comment here with what you do and what you'd like to learn, and we'll suggest a starter task.

Star + share

⭐ If AICertify resonates with you, star the repo and share it with one colleague — every star helps AI governance and policy-as-code practitioners discover the project.

[Caxha254]

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