You already run the tools. Obsidian, Ollama, Syncthing, Immich, HomeAssistant – they're installed, they mostly work, and you've spent weekends stitching them together from a dozen different blog posts that each contradict the last. What you don't have is a coherent framework that tells you *why* a piece of data lives where it does, *what* should ever touch your local AI layer, and *how* to audit the whole system when something changes. This is that framework. The Personal Data Sovereignty Stack is a threat-model-driven operating system for your personal data – not a tool tutorial, not a gear list, but a principled decision architecture that connects your threat model to your storage tiers to your AI configuration to your daily query workflows in one end-to-end system. It starts by helping you build a personal threat model that reflects your actual adversaries and risk tolerance, then runs every data type you own through a classification framework that outputs concrete storage, sync, and AI-context policies – so every downstream decision is a lookup, not a judgment call made under pressure.
What's included
- A Personal Threat Model Canvas that walks you through identifying your actual adversaries, data exposure surfaces, and risk tolerance – producing a completed threat model you can use to drive every downstream architecture decision in the system.
- A Data Classification Decision Tree covering health, communications, photos, notes, financial, and location data – a branching framework that takes any data type as input and outputs a specific storage-tier assignment, sync policy, and AI-context policy, with worked examples for each category.
- A Local-First Storage Architecture Blueprint that maps your classified data tiers to concrete storage and sync configurations – so you know exactly what lives air-gapped, what syncs locally, and what (if anything) is permitted to touch a cloud layer and under what conditions.
- Personal AI Setup Patterns covering how to configure a local model stack so sensitive context never leaves your network – including opinionated guidance on model selection, context boundaries, and the specific integration points where data sovereignty breaks down if you're not deliberate. Includes a corrected security note on Open WebUI's default network binding behavior.
- A Query Workflow System with repeatable daily, weekly, and project-scoped patterns for getting useful, ongoing output from your personal AI layer – structured so your workflows stay consistent and auditable rather than drifting into ad-hoc prompting that erodes the privacy boundaries you built.
- An Integration Map and System Audit Checkpoints section that shows how all components connect and gives you a structured quarterly review process to catch configuration drift, new data flows, or tool updates that could silently violate your threat model.
- A 30/60/90-Day Implementation Plan that sequences every major decision and configuration step across three phases – so you can build the system incrementally without having to architect everything before you can start.
