mem vs innernet
mem organises your team's work. innernet understands your thinking.
the short version
mem organises your team's work. innernet understands your thinking.
mem's own line is "let AI organize your team's work — from meeting notes, projects, to knowledge bases. All instantly searchable and readily discoverable." The subject is the team's material and the verb is organize. Both choices are deliberate and both are where we differ.
Organising is a filing problem: put things where they can be found. Understanding is a different job — reading across the material and writing down what it adds up to. And the thing being understood, for us, is a person rather than a shared drive.
(Worth clearing up before anything else: mem and mem0 are unrelated companies. mem is an AI notes and knowledge product; mem0 is memory infrastructure for developers. We compare against both, separately.)
what mem is building
An AI-organised workspace for teams. Meeting notes, projects and knowledge bases in one place, automatically arranged so nothing needs manual filing, and everything is searchable and discoverable. Web and iOS.
The original insight — that the filing is the part people never do, so the software should do it — is a good one, and self-organising notes remain a genuinely useful category.
what innernet is building
A personal memory layer that the AI tools you already use read from. npx innernet connects Claude Code, Cursor, Codex, Windsurf, Gemini CLI, Claude Desktop, VS Code, Cline, Zed and Continue to one memory, plus an MCP endpoint for the rest. netti — one per person — files what accumulates into Context Maps: dimensions that read as living documents, nodes for the people and decisions that recur, commits and branches.
netti isn't sorting your documents into the right folder. It's writing what your documents mean.
where they diverge
1. organised is not the same as understood
A perfectly organised knowledge base still requires someone to go and read it, work out what's current, and notice that two documents disagree. innernet's output is the reading: a dimension that states the decision and the reasoning, updated when the work overturns it. Search gives you candidates. A conclusion gives you an answer.
2. the team's material vs. the person's thinking
mem's subject is shared work product — notes, projects, knowledge bases. That has real value and it's a different asset from a picture of how you think. innernet's Self Map sits above every project you have, and holds what's true about the person rather than the deliverables. A team wiki has nowhere to put that, by design.
3. a destination vs. a layer
mem is a place you and your team go. innernet is not a place — it's what your existing tools read before they answer. If your memory only works when someone opens the app, it competes with everything else for attention, and attention is the thing knowledge bases reliably lose.
side by side
| mem | innernet | |
|---|---|---|
| Subject | the team's work product | the person and their reasoning |
| What the AI does | organises and surfaces | reads and writes conclusions |
| How you get value | open it and search | your other AI tools read it |
| Reachable by Claude Code / Cursor | not the surface it's built for | yes — one command |
| Structure | automatic organisation of notes | dimensions, nodes, commits, branches |
| Change over time | documents are edited | positions versioned; earlier ones kept |
| Disclosure | workspace and team permissions | per fact — private / self / trusted / work / public |
where mem is genuinely better
- Team collaboration. Shared notes and knowledge bases with the collaboration surface a team expects. We're built person-first.
- Automatic organisation. Removing the filing burden is a genuine, well-executed idea.
- Meeting notes in the same place as everything else. One workspace is a real convenience.
- A familiar shape. Everyone knows how to use a notes product; the learning curve is nearly zero.
where innernet is stronger
- A view, not a folder. netti writes what the material means, and rewrites it when the work changes.
- The memory reaches your tools. The value lands in the editor and the terminal rather than in another tab.
- Version history you can work inside. Branch a direction, park it, merge it — what you moved away from stays readable.
- Per-fact disclosure enforced on read. Connecting an AI is not the same as handing it your whole workspace.
which one you want
Use mem if your problem is that your team's notes and documents are scattered and nobody files anything.
Use innernet if your problem is that every AI tool you open knows nothing about your project, your decisions or your reasoning, and you're tired of explaining.
the question we actually get
"If AI already organises my notes, isn't that the same as memory?"
Organisation makes the past findable. Memory makes it present — already in the room when you start working, without a search. The test is simple: open a fresh session in your coding tool and ask it why you chose the database you chose. If the answer requires you to go and find the document, the memory belongs to the app, not to you.
Accurate as of 3 September 2026, based on mem's public site. mem and mem0 are unrelated companies. If we've described mem's current product incorrectly, tell us and we'll correct it.
this is what innernet remembers. you can keep your own.
innernet is memory your ai tools read live — projects, decisions, the things you’d otherwise re-explain every session. we write these letters out of ours.