Wildlab · 20 June 2026 · 4 min read
A local-first personal AI that never phones home
ElliotOS pulls from eight-plus personal data sources — health, calendar, email, productivity, news — and writes a morning and evening digest to Slack. The AI runs locally on Ollama, so none of that data has to leave the machine.
By Elliot Sturzaker
Most “personal AI assistant” products work by shipping your most personal data — your health, your calendar, your inbox — to someone else’s servers. ElliotOS is a small experiment in doing the opposite: a daily-brief assistant that reads your real life and runs the AI locally, so nothing leaves your machine unless you explicitly let it.
It’s a Wildlab project, and it’s public.
What it does
Twice a day it collects from eight-plus sources — Apple Health, macOS usage stats, Google Calendar, Gmail, Slack, nutrition, news, sport — processes them with a local model, and posts a morning and an evening digest to Slack. The morning brief is a greeting, your calendar, a health and productivity check, headlines, and a focus for the day; the evening one is a reflection, a wellness check, and a preview of tomorrow.
The processing is done by a local Ollama model by default. Cloud models (OpenAI, Anthropic) are an opt-in fallback, not the path of least resistance. No tracking, credentials in environment variables, your data staying on your hardware.
Why a studio builds this
This is a personal tool, but it’s also us thinking out loud about something we do for clients: responsible AI deployment. When the data is sensitive, “just send it to a big model’s API” is a decision, not a default — and often the wrong one. Knowing when a task can run locally, when it needs a frontier model, and how to draw that line is part of the AI-governance work we bring to real projects.
The whole thing is on GitHub if you want to read how it’s wired together.
