What I Do
I build AI systems that run locally — no cloud APIs, no subscription fees, no data leaving my machine. That means Ollama for inference, ChromaDB for vector storage, knowledge graphs for structured reasoning, and agents that operate entirely offline.
Most of what I build ends up on GitHub. I've published over 200 repositories covering everything from RAG pipelines and persona-based systems to Chrome extensions and content generation tools. Every project is working code, not demos.
Sovereign AIis the book I wrote because I couldn't find one that covered the full local stack. It walks through 11 chapters of practical implementation — running models, building pipelines, deploying agents, securing systems. No hand-waving.
By day I work with AI systems. By night I write about them and open-source the results. If you're building something local-first, I'm probably interested.
Technical Stack
AI / ML
Languages
Frameworks
Tools
Timeline
Published Sovereign AI
Released the book through Amazon KDP. 72 pages covering the full local-first AI stack — from Ollama to production deployment.
Built Sovereign Memory Bank
Open-sourced a seven-layer cognitive memory system for autonomous agent reasoning. Python, local embeddings, knowledge graphs.
Dynamic Persona MoE RAG
Developed a mixture-of-experts RAG system that routes queries to specialized personas. All local, no API calls.
Chrome AI Filename Generator
Chrome extension that renames downloads using local LLM inference. Published to Chrome Web Store.
Started Building in Public
Began open-sourcing AI projects on GitHub. Content generation systems, research assistants, graph-based retrieval.
Sovereign AI: Building Local-First Intelligent Systems
by Daniel Kliewer · Paperback · 72 pages
The hands-on guide to building AI that runs on your hardware, keeps your data private, and eliminates cloud dependence. Working code included.