The recordings of a family's everyday life are the most private data there is. So the whole system runs on a computer at home: no cloud upload, no third party in the loop.Capture on iPhone, transcribe and index on a Mac in the house, retrieve with RAG over local files. No audio, text or embeddings cross the trust boundary.
transport: private businference: localremote: WireGuard meshtrust: youThe phone, the Mac and the drive never call each other directly. They pass work across a single bus that lives inside the house, so each piece stays small, swappable and easy to audit.Producers enqueue job tickets; consumers claim, process and write results back. Loose coupling means any stage (transcribe, clean up, index) can be swapped without touching the rest.
A language model running on a Mac at home turns messy, multilingual family chatter into clean, searchable entries. It picks out the words the kids are learning, the stories worth keeping, and who said what.Local speech-to-text and an open-weights LLM segment audio into moments, tag speakers and languages, and write embeddings to a local index. Code-switching handled in the same pass.
Illustrative screens with invented entries.
Entries sit in a plain folder on a drive at home. When someone asks a question, the model retrieves from those files only, so every answer points back to something the family actually said.The corpus is plain files on local storage. Queries retrieve from that corpus only and cite the source moment, so answers are grounded rather than generated from thin air.
Away from the house, a phone connects to the home computer through an encrypted device-to-device tunnel. Only the family's own signed-in devices can see it, and it never shows up on the public internet.A WireGuard-based mesh (Tailscale) authenticates each device and builds direct encrypted paths to the Mac. No port forwarding, no public address, no cloud relay of your content.