Overview
How might we design knowledge graph so people can trust and act on AI output?
When to use
- Ideal for research tools, RAG systems, and knowledge management applications where visualizing information relationships builds trust and understanding.
When to skip
- Simple FAQ bots where a short citation list is enough.
- Mobile-first chats with no room for a graph canvas.
- Answers grounded in a single document with no meaningful relations.
Rules
Decorative graphs that do not link back to readable sources.
Hairball layouts with dozens of unlabeled nodes.
Graphs that imply certainty for weak or inferred edges.
No filter or search, forcing users to pan endlessly.
Evidence
| Product | Implementation |
|---|---|
| Hebbia | Document and concept maps for research workflows. |
| Obsidian | Local graph views of linked notes and references. |
| Roam Research | Bidirectional link graphs for knowledge bases. |
| Logseq | Outline-linked graph navigation for personal knowledge. |