An AI-powered system that automatically builds, maintains, and queries a personal knowledge graph from all your digital information - emails, documents, notes, browsing history - enabling semantic search and knowledge discovery.
Vision
Transform scattered information into an interconnected knowledge graph that reveals patterns, connections, and insights across your entire digital life.
Core Capabilities
Automated Ingestion
- Email integration (Gmail, Outlook)
- Document parsing (PDF, Word, Markdown)
- Web browsing history
- Chat logs (Slack, Discord, WhatsApp)
- Code repositories
- Calendar events
- Task managers (Notion, Obsidian)
Intelligent Extraction
- Entity Recognition: People, places, organizations, concepts
- Relationship Mapping: How entities connect
- Temporal Analysis: When information was created/modified
- Context Preservation: Original source and surrounding information
- Topic Modeling: Automatic categorization
Knowledge Graph Structure
Nodes: Entities (people, concepts, documents, projects)
Edges: Relationships (mentioned_in, related_to, created_by, depends_on)
Properties: Metadata (date, confidence, source, category)
Technical Architecture
Data Pipeline
- Ingestion: Multi-source connectors
- Processing: NLP for entity/relationship extraction
- Deduplication: Merge equivalent entities
- Enrichment: External knowledge base linking
- Storage: Graph database (Neo4j or custom)
- Indexing: Vector embeddings for semantic search
Core Technologies
- Graph Database: Neo4j or DGraph
- NLP: spaCy, transformers for entity recognition
- Vector Database: Pinecone or Weaviate for semantic search
- LLM: GPT-4 for relationship inference
- Frontend: React with graph visualization (Cytoscape.js)
Unique Features
Temporal Reasoning
- Track how knowledge evolves over time
- Identify trending topics in your life
- Predict future interests based on patterns
Connection Discovery
- Find unexpected links between concepts
- “People you should meet” based on shared interests
- “Documents you might have forgotten” suggestions
Smart Queries
Natural language queries:
- "What was I working on with John last month?"
- "Show me all projects related to machine learning"
- "Who knows about blockchain in my network?"
- "What resources did I save about React hooks?"
Privacy-First Design
- Local-first architecture
- End-to-end encryption
- Selective sharing
- Full data control
Use Cases
- Research: Connect ideas across papers and notes
- Professional Networking: Map expertise in your network
- Project Management: Visualize project dependencies
- Personal CRM: Remember details about people
- Learning: Track knowledge acquisition over time
Intelligence Layer
Pattern Recognition
- Identify recurring themes in your work
- Detect knowledge gaps
- Suggest learning paths
Proactive Insights
- “You mentioned wanting to learn X, here are resources you saved”
- “Alice and Bob both work on Y, should I introduce them?”
- “This document seems related to your current project”
Memory Augmentation
- Contextual reminders
- Relationship strengthening suggestions
- Knowledge refresh recommendations
Privacy & Security
- Local Processing: Core operations run on-device
- Encryption: AES-256 for stored data
- Access Control: Granular permissions
- Data Portability: Export your graph anytime
- Selective Sync: Choose what to backup
Visualization
Graph Views
- Force-directed graph of entities
- Timeline view of knowledge evolution
- Cluster analysis of topics
- Heatmap of activity patterns
Interaction
- Interactive exploration
- Filtering and search
- Path finding between concepts
- Subgraph extraction
Challenges
- Entity resolution across sources
- Dealing with information overload
- Balancing automation vs user control
- Performance with large graphs (100K+ nodes)
- Privacy concerns with cloud sync
Differentiation
Unlike traditional notes/bookmarks:
- Automatic: Minimal manual tagging
- Connected: Reveals relationships
- Searchable: Semantic, not just keyword
- Growing: Gets smarter over time
- Actionable: Suggests next steps
Impact
- Never forget important information
- Discover hidden connections
- Build a second brain
- Accelerate learning and creativity
- Maintain relationships more effectively
Roadmap
- Phase 1: Core graph building from documents
- Phase 2: Email and chat integration
- Phase 3: Smart querying and insights
- Phase 4: Collaboration features
- Phase 5: AI-powered knowledge curation