GhostMirror
In Active DevelopmentLocal-First AI Memory Engine
GhostMirror does not exist as a finished product. This page describes the problem it's meant to solve, the planned architecture, and current progress — not completed features, metrics, or users.
Problem
Developers lose context constantly — across terminals, notes, browser tabs, files, and coding sessions — making it hard to recall what was done, why, or where things were left off.
Vision
Build a local-first AI memory engine that automatically captures and organizes developer activity, enabling natural-language recall of previous work — entirely on-device, with no data leaving the user's machine.
Engineering Challenges
- Designing a local-first architecture that works fully offline
- Privacy-preserving storage of clipboard and filesystem activity
- Building reliable, low-overhead event collection pipelines
- Semantic retrieval and memory organization over unstructured activity logs
- Performance optimization for continuous background indexing
Planned Stack
Roadmap
- Project concept
- Repository created
- Architecture planning
- Event collection engine
- SQLite persistence layer
- Dashboard interface
- Search engine
- Embedding pipeline
- Semantic retrieval
- Public release
Planned Architecture
System Overview
How the desktop shell, backend service, and storage layer are planned to fit together.
Data Flow
Planned flow from raw activity capture to searchable memory.
Component Architecture
Major components and their planned responsibilities.