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Knowledge Graph is in early beta. It works, but it’s new and rough around the edges, and how it behaves may change. Treat it as something to try, not a finished feature to rely on.
A bucket full of memories is a list. Knowledge Graph turns one bucket into a concept map instead: it reads the memories and shows how the ideas in them connect to each other. It’s the pins-and-string view of what you’ve saved, rather than a scroll. Knowledge Graph is Pro plan only. The sidebar entry is hidden unless you’re on Pro (or higher); when it’s shown it carries a Pro badge.

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Generating a graph

1

Select a memory bucket

Open Knowledge Graph from the sidebar and pick a memory bucket. Without one selected, the page prompts you to choose a bucket.
2

Generate

Click Generate. A confirmation dialog explains that this analyzes every memory in the bucket and can take up to 30 minutes for large buckets. Confirm to start.
3

Come back for it

Generation runs in the background. You can close the page and return later; the graph shows a processing state while it builds.
Example knowledge graph: a user node with typed edges like works at, lives in, uses, owns

An example of the kind of map it builds: entities connected by typed relationships.

Knowledge Graph page showing a concept map with nodes like You, Northwind, and Design System connected by typed edges such as works at, leads, and uses

A generated knowledge graph: concepts as nodes, typed relationships as labelled edges. Click a node to see how it connects.

To rebuild after adding memories, use Regenerate, which replaces the existing graph with a fresh one.

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Good to know

  • It’s per bucket. Each graph maps a single bucket, not your whole account.
  • It can take a while. Building a graph uses AI and can take up to 30 minutes for a large bucket. This isn’t instant, and that’s expected.
  • Memory buckets only. Point it at a bucket that has memories in it.

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Next steps

Memory Buckets

Organize memories into the buckets a graph is built from

Smart Memory

Group a bucket into categories for token-efficient recall