Your meetings. Your data. Your machine.
Free, open-source meeting intelligence with a learning digital twin — running entirely on your desktop. Record a meeting and the app becomes that session: a profiled AI assistant works alongside you, everything said turns into a living, searchable knowledge graph, and nothing ever leaves your computer.
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lifedash-demo.mp4
LifeDash records your meetings, transcribes them locally with Whisper, and generates briefs and action items — all offline, no accounts. But it goes further than a transcriber: the recording session is the center of the app.
A Digital Twin — built from a profile of your work and continuously learning from every session — works visibly alongside you during a meeting, answering questions and proposing and creating cards on a built-in Kanban board. Everything it hears builds a living, queryable brain (sessions → projects → cards → decisions → people) that you can watch grow as a mind map and search in plain language — "what did we decide about pricing?" — answered, with citations, from your own past meetings.
All of it runs 100% locally by default — audio, transcription, reasoning, embeddings, and memory never have to leave the machine. Cloud is a per-task, clearly-labeled opt-in.
| Platform | Status |
|---|---|
| Windows 10+ | Available. Download the installer |
| macOS 12.3+ (Monterey) | Beta. brew tap lab-51/lifedash && brew install --cask lifedash (manual install) |
| Linux | Planned. Contributions welcome |
| Feature | LifeDash | Otter.ai | Fireflies | Fathom |
|---|---|---|---|---|
| Local processing | Yes | No | No | No |
| Data leaves your machine | Never | Always | Always | Always |
| Works offline | Yes | No | No | No |
| Meeting transcription | Yes | Yes | Yes | Yes |
| AI briefs & summaries | Yes | Yes | Yes | Yes |
| Action item extraction | Yes | Yes | Yes | Yes |
| Project management | Yes | No | No | No |
| Learning digital-twin assistant | Yes | No | No | No |
| Ask your own meetings (cited, local) | Yes | No | No | No |
| Bring your own AI key | Yes | No | No | No |
| Open source | Yes | No | No | No |
| Price | Free | $204/yr | $216/yr | $384/yr |
Just want to use it? Grab the installer. No dev tools needed.
- Go to the latest release
- Download
LifeDash-X.X.X-Setup.exe - Run the installer
- Open LifeDash, add your AI API key (or point it at a local model) in the setup wizard, and start recording
Option A — Homebrew (recommended):
brew tap lab-51/lifedash && brew install --cask lifedashOption B — Direct DMG download:
- Download
LifeDash-X.X.X-mac-arm64.dmgfrom the latest release - Open the DMG, drag LifeDash to Applications
- Important: macOS will show "LifeDash is damaged" because the app is not yet Apple-notarized. Run this once to fix it:
xattr -cr /Applications/lifedash.app
- Open LifeDash normally
Requires macOS 12.3 (Monterey) or later. Apple Silicon only (M1/M2/M3/M4).
The app uses an embedded database and runs fully offline. No accounts, no cloud, nothing to configure beyond the installer.
- The recording session is home — Transcript · Board · Brain on one switchable canvas
- A live rail for the brief, action items, twin proposals, and a session activity feed
- The relevant Kanban board is embedded right in the session — cards appear and move live as they're created, without leaving the conversation
- Post-meeting, each session is its own full page you can revisit, search, and continue working from
- Author a profile of the professional you are — through a guided wizard (fully manual, or with an optional local-AI "Interview me" draft you always review), from a short brief, or mined from your own meeting history with explicit per-run consent
- Once authored, the Twin is woven into the live assistant, live triage, and briefs — so they speak your vocabulary, track your projects and people, and match your tone, within a strict budget that never crowds out the meeting
- It learns from every finished session — distilling a few durable facts (people, projects, preferences, commitments) into an auditable memory: every fact links to the session it came from, one tap forgets it for good, and a single switch pauses all learning
- Optional cited web research and deep, orchestrated profile creation on a frontier provider — nothing is saved until you confirm
- Record system audio + microphone
- Real-time transcription (local Whisper or cloud providers)
- AI-generated meeting briefs and summaries
- Automatic action item extraction, turned into board cards in one click
- Speaker diarization and meeting analytics
- A proactive in-meeting assistant that proposes actions (propose → one-tap accept) and executes board work as you talk
- A collapsible mind map of your workspace — or a single session — rendered from your own local data
- It grows live during a meeting: new cards fade in, with a badge on collapsed branches so nothing is missed
- Hover any card, decision, or question to trace its provenance back to the session it came from
- Its first semantic layer: the people and topics from each meeting become entities linked across every session they appear in
- Full-text search across sessions, transcripts, briefs, cards, and projects — grouped, ranked, one click to jump in
- Semantic search: a paraphrase finds the right session even when the words don't match
- Ask: get a short, cited answer drawn straight from your own sessions — and an honest "I don't find that in your sessions" instead of a guess
- Local-first: the index is built on-device by default; choosing a cloud embedding model warns you, at that moment, that your content would be sent — it never happens silently
- Turn action items into Kanban cards, seen through the sessions that created them
- Drag-and-drop cards with customizable columns
- Card detail view with rich text, comments, checklists, due dates, labels, and tags
- Card & Project Agents (tool-calling AI per card/board) and background agents for autonomous stale-card detection and project insights
- All data stored locally in embedded PostgreSQL (PGlite); audio recordings stay on your machine
- Local reasoning (LM Studio / Ollama) and local embeddings by default — cloud is a per-task, visible opt-in that warns before sending bulk content
- AI uses YOUR API keys. We never see your data
- Optional cloud sync (Supabase) — off by default, fully opt-in
- Encrypted API key storage via OS keychain
- Factory reset with full data deletion
- Open source. Read the code yourself
- Crash recovery — The app takes periodic snapshots of your work. If it shuts down unexpectedly, you get a recovery dialog on next launch to restore exactly where you left off
- Database integrity checks — Every startup verifies your data is intact across all tables, with automatic retry if the database is slow to connect
- Atomic backup/restore — Restores run inside a database transaction. If anything goes wrong mid-restore, the whole thing rolls back and your original data stays untouched
- Structured logging — Daily log files with automatic rotation make it easy to diagnose issues without digging through console output
- Graceful AI degradation — If your AI provider is down or misconfigured, you get fallback behavior and clear error messages instead of crashes or silent failures; learning and semantic-index jobs are error-isolated so they can never break a brief
- Keyboard accessible — Every modal traps focus properly, cycles with Tab/Shift+Tab, and closes with Escape. Screen readers work out of the box
- Input validation everywhere — Every IPC channel validates its inputs at runtime with Zod schemas, not just at compile time
- Optional crash reporting — Opt-in Sentry integration strips all personal data (file paths, API keys) before sending. Off by default, always under your control
- "What's New" on update — After each update, a release notes modal shows what changed so you always know what's new
For developers and contributors. Most users should download the installer instead.
- Node.js 18+ (includes npm)
- Git
- Windows: Visual Studio Build Tools with "Desktop development with C++" workload (needed for native modules)
- macOS: Xcode Command Line Tools (
xcode-select --install)
git clone https://github.com/Lab-51/lifedash.git
cd lifedash
npm install
npm startNo database setup. The app uses PGlite (embedded PostgreSQL) and runs migrations on first launch.
- AI API keys: Set them in the Settings page. Keys are stored using OS-level encryption via Electron safeStorage.
- Local models: Point any task at LM Studio or Ollama for fully-private reasoning. Semantic search needs a local embedding model (e.g. a multilingual EmbeddingGemma-300M-class model in LM Studio) assigned to the Embedding task.
- Whisper model: Download and manage local Whisper models from Settings.
- Transcription providers: Deepgram and AssemblyAI can be configured as cloud alternatives to local Whisper.
- Cloud sync: Optionally sign in with Supabase to sync data across devices. Off by default.
- Data export: Export your entire database as JSON or CSV from Settings > Data & Storage.
| Problem | Solution |
|---|---|
npm install fails with node-gyp errors |
Install Visual Studio Build Tools with C++ workload |
npm install fails with Python errors |
Install Python 3.x and set npm config set python python3 |
| App shows white screen on start | Run npm run lint to check for TypeScript errors |
| Script | Description |
|---|---|
npm start |
Launch in dev mode |
npm run package |
Package for distribution |
npm run make |
Build platform installers |
npm run lint |
Type-check with TypeScript |
npm test |
Run tests |
npm run test:watch |
Run tests in watch mode |
npm run db:generate |
Generate migration files |
npm run db:migrate |
Apply migrations |
npm run db:studio |
Open Drizzle Studio (database GUI) |
| Category | Technology |
|---|---|
| Runtime | Electron |
| Frontend | React 19 + TypeScript |
| Styling | Tailwind CSS 4 |
| Database | PGlite (embedded WASM PostgreSQL) + pgvector |
| ORM | Drizzle ORM |
| AI SDK | Vercel AI SDK |
| AI Providers | OpenAI, Anthropic, Google (Gemini), LM Studio, Ollama, Kimi |
| Embeddings | Local by default (LM Studio) — on-device semantic index |
| Semantic search | pgvector (HNSW) + Postgres full-text, hybrid RRF fusion |
| Transcription Providers | Deepgram, AssemblyAI |
| Transcription | @fugood/whisper.node (local) |
| Brain / mind map | d3-hierarchy + d3-zoom (event-driven SVG) |
| Drag and Drop | @atlaskit/pragmatic-drag-and-drop |
| State | Zustand |
| Rich Text | TipTap |
| Animation | Framer Motion |
| Icons | Lucide React |
| Routing | React Router |
| Build | Vite |
| Cloud Sync | Supabase (optional) |
| Testing | Vitest |
src/
main/ # Electron main process
db/ # Schema, migrations, connection (PGlite + pgvector)
ipc/ # IPC handlers (100+ channels)
services/ # Business logic (AI, transcription, twin, embeddings, brain, backup)
workers/ # Background workers (transcription)
preload/ # Electron preload bridge
renderer/ # React frontend
components/ # Session workspace, Twin, Brain mind map, Board, Settings, UI
hooks/ # Custom React hooks
pages/ # Route pages (Sessions, session detail, Twin, Board, Settings)
services/ # Frontend service layer
stores/ # Zustand state management
styles/ # Global styles
shared/ # Types and utilities shared across processes
Contributions are welcome! See CONTRIBUTING.md for guidelines on reporting issues and submitting pull requests.
This project is licensed under the GNU Affero General Public License v3.0. For commercial licensing inquiries, contact the author directly.