Skip to main content

​
What is xysq?

xysq is a context engineering platform. You capture raw AI work: session transcripts from tools like Claude, Cursor, and ChatGPT, plus files you upload. The xysq Memory Engine distills that into your context lake. Your agents and your team read from the lake. When something in it is wrong, you correct it once and the engine applies the fix everywhere it matters. The flow, end to end:
Most memory systems accumulate. Yours should improve. That is the difference the engine is built around: every piece of context traces back to a verbatim source, every change lands as a diff you can read, and a correction is served as soon as the engine has applied it.

​
The shape of it

Three terms carry the whole model:
  • Context lake. One per user or team. It holds everything the engine has distilled from your AI work, organized as context graphs.
  • Context graphs. A lake holds many of them: Personal (yours), Teams (shared with your team), and Agents (the ones your code creates). Scope agent graphs however your product needs: one per app, per workload, per customer, or several agents sharing one. An agent key reaches only agent graphs, and only the ones it has been granted.
  • The xysq Memory Engine. The machinery underneath every graph. Immutable verbatim logs at the bottom. Distilled, readable pages on top. Every fact cites the log it came from, and no change happens outside a checked, recorded run.
Your AI tools connect over MCP. They push what happened, verbatim, and pull assembled context back. All the real work (extraction, deduplication, structuring, ranking) happens server-side in the engine, not in the tool.

​
Correct once, and it improves

When the engine has something wrong, you do not re-explain it in every session. You correct it once. One gated run closes the old fact, rewrites every page that carried it, and stops serving it. Ask again and you get the corrected state. Nothing lands halfway. A change the engine cannot apply cleanly (an edit it cannot account for byte for byte, a page that shrank more than the run declared) is refused as a whole batch and retried, so your pages are never left half-updated.

​
Ownership

Your lake is yours. Pages are plain markdown, every change is a commit you can diff, you can read any source back byte for byte, and deleting a source or a whole graph really removes it. Bring your own storage and private deployment are the direction we are building, not shipped yet.

​
Where to go next

Quickstart

Connect a tool, push a session, correct a fact. About ten minutes.

Concepts

The context lake, context graphs, and how the engine distills and improves.

MCP reference

The four tools: userinfo, push_context, pull_context, share_context.