Heptabase is a beautiful tool for spatial thinkers. But cards on a canvas are only one way to see your knowledge. Synap gives you the whiteboard AND the table AND the kanban AND the graph — all over the same structured data.
Heptabase's cards are flexible — but they're all the same thing. A research paper card looks identical to a task card or a person card. There are no typed properties, no schema, no way for software to understand what a card represents.
In Synap, entities have profiles: a paper has authors, a publication date, and citations. A task has a status, priority, and assignee. A contact has an email and a company. This structure is what makes AI useful — it can reason about your data because it understands what things are and how they relate.
Heptabase's strength is its canvas. But what if you want to see your tasks on a kanban board? Your events on a calendar? Your knowledge as a network graph? Heptabase gives you one paradigm. Synap gives you sixteen interchangeable views over the same data: table, kanban, calendar, gallery, masonry, flow, whiteboard, and more. Switch views instantly without reorganizing anything.
Heptabase has basic AI features, but the organizing is still on you. You drag cards, create whiteboards, manually arrange spatial layouts. In Synap, AI agents understand your entity graph. Drop in a research paper and the AI extracts metadata, links it to related topics, identifies key authors, and suggests connections to your existing knowledge — all through reviewable proposals.
Heptabase is a closed SaaS product with no self-hosting and limited API. Synap is built on an open protocol with a full tRPC API, a developer SDK, and the option to self-host your data pod. Your knowledge infrastructure should be as portable as your knowledge itself.
