Build confidence in your AI with systematic slice-based testing
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Updated
Jun 26, 2025 - Python
Build confidence in your AI with systematic slice-based testing
practical handbook and resources for establishing AI governance frameworks, covering ethics, risk, compliance, and maturity models. View live at: https://khullani.github.io/AI-Governance-Handbook/
CAIR4 Explorer Light is a modular, Streamlit-based framework for regulatory analysis of AI use cases, using advanced models like GPT-4, Claude, Groq, Gemini, and more. This lightweight edition includes a curated subset of the full CAIR4 library (80+ use cases), offering a fast and focused entry point. The default interface and content are in German
Aspiring AI & Data Analyst | Focused on Chatbots, Prompt Engineering & AI Governance | Learning Python & Streamlit by building real projects
Proposed AI strategy for UNIQA focused on regulatory compliance, risk management, and ethical deployment under the AI Act
/a futuristic, Matrix-style website that visually and interactively presents the landscape of next-generation AI regulations, inspired by the EU AI Act (reference: https://artificialintelligenceact.eu/ai-act-explorer/).
ai-praxis-tool
Rule-based chatbot prototype exploring conversational AI through compliance-inspired prompts and ethical design logic.
Legal analysis of liability challenges in AI under EU law (based on EC report)
This is my first repository @ Github! -> Core Net AB (Information Security, Privacy, Governance, Legal, Compliance, and Risk Management).
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