A note per source
Claims, quotes, and your team's read on it. Wikilinks tie sources to the questions they bear on, and backlinks show every question a source touches.
A research team's real output is not the final report; it is the accumulated web of sources read, claims tested, dead ends marked, and findings connected. Most teams keep that web in scattered docs and one senior person's intuition. Memava makes it a shared, attributed, linkable asset.
In research, "who says so" matters as much as "what". Every note in the vault carries its author and full history, so a claim traces to the person or the AI that filed it, and to every revision since. When an agent summarizes twenty papers overnight, its notes are marked as its own: useful, checkable, and never mistaken for a human's judgment.
An AI's literature notes are labor saved only if you can tell they are the AI's. Attribution is what makes machine reading trustworthy.
Claims, quotes, and your team's read on it. Wikilinks tie sources to the questions they bear on, and backlinks show every question a source touches.
Each open question is a note that collects evidence for and against as links. The graph view literally draws the state of your investigation.
Point your AI at the unread pile; it files structured notes under its own name for humans to verify and connect. Reading scales; judgment stays human.
Unpublished work stays in restricted folders; the same rules bind collaborators and AI. Share when ready, not when leaked.
Honest limit: search today is full text, not semantic; embedding search is on the roadmap and we say so before you sign anything.
Keep reading: How to give AI agents a real, shared memory · CLAUDE.md, AGENTS.md and a shared team memory · Connect Claude to a shared team memory