Your Personal Semantic Engine — turns scattered thoughts, notes, emails, and messages into an intelligent, searchable knowledge graph with predictive insights.
Einstein captures context from every tool you use — email, Slack, GitHub, Jira, Zoom, meetings, notes — and weaves it into a single knowledge graph. It surfaces what matters: who's going dormant, what's overdue, which relationships need attention, and what's likely to happen next.
- Semantic Knowledge Graph — entities, relationships, and topics extracted automatically from your notes and events
- Interactive Graph View — explore connections between people, projects, and ideas visually
- Smart Search — natural language queries across your entire knowledge base
- Ask AI (RAG) — conversational Q&A grounded in your own data
- Vault Notes — Markdown-first note-taking with folders, frontmatter, outgoing links, and version history
- Meeting Briefings — auto-generated prep packs before calls
- Action Items — extracted from notes and tracked across projects
- Decisions Log — record reasoning, alternatives, and revisit dates
- Calendar Events — linked to notes and people
- People Profiles — auto-built dossiers from every interaction
- Dormancy Detection — flags relationships going cold before they break
- Freshness Scoring — quantifies how active each connection is
- Interaction Timeline — full history per person
- Project Tracking — status, deadlines, linked notes, associated people
- Activity Monitoring — dormancy alerts for stale projects
- Cross-linking — notes, actions, and events connected to projects automatically
- Activity Heatmap — 60-day activity patterns across all sources
- Trend Detection — increasing, decreasing, or stable activity analysis
- Forecasting — time-series predictions using statistical models (Holt-Winters) with optional deep learning backends
- Dormancy Risk — predictive alerts for people and projects at risk of going inactive
- Forecast Accuracy — retrospective MAPE, MAE, and coverage tracking
- Gmail — auto-capture emails
- Outlook — Microsoft email sync
- Slack — channel messages
- GitHub — PRs, issues, reviews
- Jira — issue tracking
- Zoom — meeting transcripts
- Linear — project tracking
- Telegram — bot messages & channels
- Google Calendar — event sync (via Gmail)
- OAuth2 Flows — connect with one click, credentials stored securely
- Webhook Ingestion — real-time event capture
┌──────────────────────────────────────────────────────────────┐
│ React Frontend (Vite) │
│ BrainHome · Graph · Files · People · Projects · Insights │
│ Meetings · Actions · Ask AI · Integrations · Calendar │
└──────────────────────┬───────────────────────────────────────┘
│ REST API
┌──────────────────────▼───────────────────────────────────────┐
│ FastAPI Backend │
│ 15 route modules · Auth middleware · Error handlers │
├──────────────────────────────────────────────────────────────┤
│ Domain │ Application │ Infrastructure │
│ · Entities │ · Use Cases │ · PostgreSQL │
│ · Repositories │ · Orchestration │ · Pinecone (vector) │
│ · Services │ · Validation │ · Redis + ARQ │
│ │ │ · 9 Connectors │
│ │ │ · Forecasting │
└──────────────────────────────────────────────────────────────┘
| Layer | Technologies |
|---|---|
| Frontend | React 18, TypeScript, Vite, Tauri (desktop), Lucide icons |
| Backend | Python 3.11+, FastAPI, Pydantic v2, SQLAlchemy (async) |
| Database | PostgreSQL 13+ with asyncpg |
| Vector Search | Pinecone, OpenAI embeddings |
| AI / LLM | OpenAI GPT, LiteLLM |
| Background Jobs | ARQ + Redis (cron workers, sync tasks) |
| Auth | JWT (python-jose), bcrypt |
| Deployment | Vercel (serverless), Docker |
Einstein supports two modes: Local (everything on your machine) and Cloud (managed services). The in-app Getting Started wizard walks you through either path with live status checks.
# 1. Clone & install
git clone https://github.com/Phani3108/Einstein.git
cd Einstein
pip install -e '.[local]'
# 2. Install Ollama (local AI) — https://ollama.com
ollama pull llama3.2
ollama pull nomic-embed-text
# 3. Configure
cat > .env << 'EOF'
DATABASE_URL=sqlite+aiosqlite:///einstein.db
LLM_MODEL=ollama/llama3.2
OLLAMA_BASE_URL=http://localhost:11434
EMBEDDING_PROVIDER=ollama
EMBEDDING_MODEL=nomic-embed-text
EOF
# 4. Start
uvicorn src.api.app:app --reload --port 8000
# 5. Frontend (new terminal)
cd app && npm install && npm run devOpen http://localhost:5173 — click Getting Started in the sidebar.
# 1. Clone & install
git clone https://github.com/Phani3108/Einstein.git
cd Einstein
pip install -e .
cd app && npm install && cd ..
# 2. Configure
cp .env.example .env
# Edit .env with your credentials:
# DATABASE_URL=postgresql+asyncpg://user:pass@host/dbname
# OPENAI_API_KEY=sk-...
# LLM_MODEL=gpt-4
# 3. Initialize & run
python scripts/init_db.py
uvicorn src.api.app:app --reload
cd app && npm run dev| Mode | Requirements |
|---|---|
| Local | Python 3.11+, Node.js 18+, Ollama |
| Cloud | Python 3.11+, Node.js 18+, PostgreSQL, OpenAI API key |
curl -X POST http://localhost:8000/api/v1/dev/seedEinstein/
├── app/ # React frontend (Vite + TypeScript)
│ └── src/
│ ├── components/ # 40+ UI components
│ ├── lib/ # API client, state management
│ └── App.tsx # Root with onboarding flow
├── src/ # Python backend
│ ├── api/ # FastAPI routes (15 modules)
│ ├── application/ # Use cases & orchestration
│ ├── domain/ # Entities, enums, interfaces
│ └── infrastructure/ # DB, connectors, prediction, tasks
├── scripts/ # DB init, seeding, utilities
├── migrations/ # Alembic database migrations
├── tests/ # Test suite
├── browser-extension/ # Chrome extension (capture)
├── mobile/ # Mobile app scaffold
└── einstein-cli/ # CLI tool
| Group | Prefix | Purpose |
|---|---|---|
| Vault | /api/v1/vault |
Notes, decisions, config, files |
| Thoughts | /api/v1/thoughts |
Thought capture & retrieval |
| Search | /api/v1/search |
Semantic + hybrid search |
| Context | /api/v1/context |
Events, people, projects |
| Insights | /api/v1/insights |
Briefings, activity, dormancy |
| Actions | /api/v1/actions |
Action items CRUD |
| Integrations | /api/v1/integrations |
OAuth connect, sync, webhooks |
| Predictions | /api/v1/predictions |
Forecasts, accuracy, status |
| Intelligence | /api/v1/intelligence |
AI analysis & suggestions |
| AI Tools | /api/v1/ai |
Ask AI (RAG), summarization |
| Timeline | /api/v1/timeline |
Chronological event view |
| Reflection | /api/v1/reflection |
Weekly digests, patterns |
| Distillation | /api/v1/distillation |
Note condensation |
| Admin | /api/v1/admin |
User management, health |
| Dev | /api/v1/dev |
Seed data (dev only) |
Interactive docs available at /api/v1/docs when the server is running.
The seed script creates a realistic, interconnected dataset for a startup founder building "Nexus":
- 7 people — co-founder, designer, engineer, investor, advisor, customer, freelancer
- 4 projects — MVP, fundraising, marketing, enterprise pilot
- 15 vault notes — meetings, journals, specs, brainstorms, decisions
- 10 action items — varied priorities, statuses, and deadlines
- 6 calendar events — upcoming meetings and reminders
- 30 context events — emails, Slack, GitHub, calendar across 60 days
- 16 semantic entities — people, orgs, topics, technologies
- 11 entity relationships — builds, works_at, advocates, implements
- 4 decisions — with reasoning and alternatives
- 4 commitments — tracked promises to people
All data is idempotent and can be re-run safely.
The project deploys as a monorepo on Vercel:
- Frontend — built with
npm run buildfromapp/, served as static files - Backend — Python serverless function via
api/index.py - Config — see
vercel.jsonfor routing rules
Set DATABASE_URL, OPENAI_API_KEY, PINECONE_API_KEY, and JWT_SECRET in the Vercel dashboard.
- Fork the repository
- Create a feature branch:
git checkout -b feat/your-feature - Follow conventional commits:
feat:,fix:,refactor:,docs: - Push and open a pull request
MIT — see LICENSE for details.