AI Consultant · Muslim Hands (NGO)
Prototype
Internal record → 🛡 automated redaction → LLM
?
Detected identifiers
LLM-safe output
Fictional data, editable — the same automated-redaction idea from the GDPR-compliant AI data strategy: strip direct identifiers before any text reaches an LLM. Detection here is a regex + heuristic stand-in for the real workflow's redaction layer.
Highlights
- Strategic Advisory: Advised senior executives (Deputy CEO & Senior Management Team) on systemic AI adoption, identifying 3+ high-impact use cases that streamlined planning and mitigated operational risks in 2 core departments.
- Data Privacy Strategy: Developed a secure AI data strategy and risk framework report, enforcing GDPR compliance through structured AI workflows and automated redaction strategies for internal systems.
- Executive Training: Designed, led, and facilitated 3+ interactive corporate training workshops on prompt engineering and LLM tools to optimize internal stakeholder technical fluency.
- Scoping Future Use Cases: Maintained ownership of high-level executive deliverables (AI Use Case & Risk Report, Training Plan), translating abstract technical concepts into strategic roadmap items including secure chatbots and AI-driven fraud detection.
Technologies
- GDPR Compliance
- Prompt Engineering
- LLM Tools
- AI Agents
- Fraud Detection