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Kiori vs Heptabase
AI Knowledge Platform vs Visual PKM Whiteboard
The short version
Heptabase is one of the tools I watch most closely. It's a visual knowledge management tool built around infinite whiteboards. You place cards on a canvas, draw connections, and think spatially. It's excellent for sense-making and research synthesis, and the team behind it clearly cares about the craft.
Kiori also has visual canvases, but it's a different kind of tool. You upload documents, build pages, organize on canvases, and query everything with AI that cites its sources. The emphasis is on retrieval and compounding, not just spatial arrangement.
Both are visual. They differ in what happens after you organize.
Feature Comparison
| Feature | Kiori | Heptabase |
|---|---|---|
| AI retrieval | Built-in — natural language Q&A with confidence scores and source citations | AI chat available (multi-model), but no confidence grounding or citation verification |
| Visual canvases | 14+ card types, drag-and-drop, folders, nested canvases | Infinite whiteboards with ~5 card types. Whiteboard is the core paradigm. |
| Knowledge compounding | Automatic re-indexing when content updates. Knowledge flywheel. | Manual — you curate and connect cards yourself |
| Editor | Block editor — 30+ block types, slash commands | Card-based editor — clean but more limited |
| Public sharing | Native public workspaces — visitors can ask AI questions | No public sharing |
| Document import | 15+ formats with OCR (PDF, DOCX, XLSX, slides, images) | PDF annotation and import. Limited other formats. |
| Team collaboration | Built-in — shared workspaces | Real-time collaboration on whiteboards |
| AI content understanding | Reads all document types including images and embedded content | Cannot reliably read images, videos, or embedded cards |
When to choose Heptabase
- •Spatial thinking is your primary workflow — you need the whiteboard to be the core experience, not a feature
- •You do deep research synthesis and want to lay out sources visually to find connections
- •You want strong PDF annotation with highlights that become cards on your whiteboard
- •Real-time collaboration on visual boards is a priority
- •You prefer a simpler, more focused tool at a lower price point
- •You don't need public sharing or AI with confidence grounding
When to choose Kiori
- You want AI retrieval with confidence scores and verifiable source citations
- You need 14+ card types for richer knowledge representation, not just text cards on a whiteboard
- You want automatic re-indexing so your knowledge compounds without manual curation
- You need to share knowledge publicly — wikis, community pages, help centers
- You need to import and query across many document types (not just PDFs)
- You care about EU data residency and clear privacy commitments
- You want a free tier to start without committing to a paid plan
The curation gap
Heptabase's strength is manual curation. You read a paper, highlight passages, drag cards onto a whiteboard, and draw connections. That process is where insight happens. I respect that approach.
The tradeoff is that everything requires your hands. Every connection is manual. Every card placement is intentional. That's powerful for deep research sessions, but it doesn't scale. The knowledge you curated last month doesn't automatically surface when it's relevant to what you're working on today. I hit that wall myself with hundreds of documents across projects. Manual curation was the first thing to break down.
That's why I built Kiori's retrieval layer the way I did. Knowledge you added weeks or months ago is still findable through natural language queries with cited answers. You still get visual canvases for spatial thinking, but the AI layer ensures nothing falls through the cracks when your knowledge base grows past what you can manually tend.
If your workflow is primarily deep research sessions where manual curation is the point, Heptabase is genuinely great at that. If you want visual organization plus retrieval that scales, that's the gap I'm trying to fill.