Tana hands you the most powerful knowledge-modelling toolkit on the market; Pith hands you the finished, cited wiki without the modelling work.
Tana is an outliner with Supertags — structured fields you attach to any node and query into live dashboards — plus AI meeting agents and multi-model AI. It is enormously capable, and also something you have to architect and maintain yourself. Pith takes the opposite stance: you bookmark what you read, and it auto-builds a cited wiki and per-client briefings where every claim links to a source. Tana rewards people who love building systems; Pith is for people who want the source-grounded output without becoming a database administrator.
Side by side
| Attribute | Pith | Tana |
|---|---|---|
| Authoring model | Auto-built from what you bookmark | You design supertags and structure manually |
| Learning curve | Read, bookmark, get a wiki | Powerful but steep; system-building required |
| Source grounding | Every claim links to a saved source | Structured nodes; citations are manual |
| Per-client briefings | Auto-generated, source-cited briefings | Buildable via supertags and live queries |
| AI access (MCP) | Hosted MCP for cited querying | Local MCP via desktop app on localhost |
| AI features | Synthesises cited wiki and briefings | Meeting agents, multi-LLM, AI commands |
| Data residency | Hosted in Frankfurt (EU) | Cloud-hosted; EU residency not advertised |
| Structure model | Wiki entries grounded in sources | Supertags, nodes, references, live searches |
| Collaboration | Shared wiki and briefings | Team workspaces with admin controls |
| Pricing model | Free to save; pay per deliverable (€2–€5). No subscription | Free, Plus $10, Pro $18, Team $18/user |
| AI credits | No meeting-minute credit metering | Monthly AI credits meter usage |
| Best for | Turning reading into cited knowledge fast | System-builders modelling rich structured data |
When Pith wins
You want the output, not the build
Pith produces a cited wiki and briefings automatically from your reading, with no schema to design. Tana can model almost anything, but you first have to architect supertags, fields, and queries — and keep them maintained.
Claims must trace to a source
Pith grounds every statement in a saved source, so a briefing is auditable point-by-point. Tana structures your data beautifully, but source citations are something you wire in yourself rather than a built-in guarantee.
EU hosting is a requirement
Pith hosts data in Frankfurt, which matters for DACH consultancies and GDPR-sensitive clients. Tana does not advertise EU-specific data residency, and its MCP access runs locally through the desktop app rather than as a hosted EU service.
Where Tana wins
You want to model complex structured data your own way
Tana's Supertags, live queries, and dashboards are genuinely best-in-class for people who want to design their own knowledge schema, run AI meeting agents, and switch between multiple LLMs. If you enjoy building a bespoke system and need rich structured querying, Tana does far more than Pith's focused reading-to-wiki workflow.
FAQ
How is Pith different from Tana at a glance?
Tana is a build-it-yourself structured workspace; Pith is an auto-built, cited wiki from your reading. With Tana you design the system, with Pith the system is the product and the output is source-grounded by default.
Does Tana cite sources automatically?
No. Tana gives you structured nodes and powerful queries, but linking a claim to its source is manual modelling work. Pith makes source grounding the default — every claim links back to a saved source.
Do both tools support MCP?
Both do, but differently. Tana exposes a local MCP server through its desktop app on localhost while the app is open. Pith offers a hosted MCP so assistants can query your reading memory and answer with citations.
Which has the steeper learning curve?
Tana is widely described as powerful but steep — supertags and queries reward investment. Pith is deliberately narrow: you read, bookmark, and receive a cited wiki, with no schema to learn.
Where is data hosted?
Pith hosts in Frankfurt, in the EU, which is a deciding factor for many DACH and GDPR-bound teams. Tana is cloud-hosted but does not advertise EU-specific residency, so confirm with them if that is a hard requirement.
Can Tana generate per-client briefings?
You can build briefing-like views with supertags and live queries, but you assemble and maintain that yourself. Pith generates per-client briefings automatically, each point cited to the source behind it.
How does pricing compare?
Tana has a free plan, Plus at $10/month, Pro at $18/month, and Team at $18/user, with AI credits metering usage. Pith is free to save and charges per deliverable — €2 for a cited briefing from your saved sources, €5 for a dossier over your corpus, €3 for audio — rather than metering AI credits.
Should I pick Tana over Pith?
Choose Tana if you love building a custom structured system, want AI meeting agents, and need multi-LLM flexibility. Choose Pith if you want source-grounded wiki output from your reading without building or maintaining the structure yourself.
Last reviewed: 7 June 2026 · CC BY 4.0 · cite freely with attribution to Pith.