What problem does it solve?
Helps you organize scattered ideas, sources, and insights into a connected graph so you can discover relationships, surface gaps, and synthesize research across domains without manual spreadsheet or note juggling.
Core Features & Use Cases
- Concept Linking & Tagging: Create bidirectional links between concepts, label relationship types (causes, enables, contradicts) and record confidence/context.
- Source & Citation Networks: Attach sources to claims, map supporting and contradicting evidence, and surface citation clusters for literature reviews.
- Querying & Visualization: Trace relationship chains, find related concepts, highlight high-centrality nodes, and show textual graph summaries or cluster views.
- Inference & Gap Analysis: Infer transitive or implicit links, detect contradictions, identify isolated concepts, and recommend areas to investigate or validate.
- Progressive Automation: Start with manual mapping (guided), advance to automatic inference and pattern detection, and use predictive insights for strategic research planning.
- Use Case Example: Build a literature-review graph from 15 papers to find underexplored verification methods and prioritize next readings.
Quick Start
Ask the assistant to "Build a knowledge graph from my 15 LLM safety papers, list major clusters, and highlight gaps to investigate."
