Most organizations run AI agents that call external APIs, handle customer data, and make autonomous decisions — without knowing where the data goes, who authorized the call, or where the response is stored.
I fix that.
What I work on:
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Agentic AI Security — prompt injection defense, tool contracts, circuit breaker patterns for autonomous AI systems
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Sovereign AI Infrastructure — local inference on Apple Silicon (MLX, vLLM), EU-compliant model governance, cloud exit strategies
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Enterprise AI Architecture — RAG pipelines, AI gateways, and compliance evidence chains under EU AI Act, GDPR & NIS2
Writing:
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Medium — Patterns for sovereign AI that survive Monday morning
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LinkedIn — Posts on AI security & enterprise architecture
Open Source:
- 🛡️ Prompt Injection Guard — Two-stage detection for Claude Code agents with local LLM classification
- 🍎 apple-silicon — Sovereign AI inference on Apple Silicon — MLX, containerization, and local model deployment
- ⚡ sovereign-vllm-metal — vLLM on Apple Silicon Metal — step-by-step sovereign inference setup
- 🐳 claude_in_devcontainer — Run Claude Code in isolated dev containers for secure agentic workflows
- 📊 pbi-mcp-wiki-generator — Auto-generate documentation wikis from Power BI datasets via Power BI MCP server
- 🔑 appcredmon — Monitor and alert on expiring app credentials in Azure/Entra ID
📍 Germany · Founder of bluetuple.ai