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The simple casePersonal AI

One memory across all your AI.

Whatever you tell one assistant is there in the next. Your notes, preferences, and context follow you across every tool — instead of starting over each time.

One connected memory, feeding whichever assistant you use
shared bucketYouNotesPreferencesProjectsPeopleChatGPTClaude
  • parent
  • subagent
  • peer
  • tool
The relatable problem[1 / 5]

Every tool is a fresh stranger.

You told ChatGPT your preferences on Monday and your other assistant has no idea on Tuesday. Every tool is a fresh stranger.

Before · 01

Each tool starts from zero

Switch apps and you're a stranger again — none of what you taught the last one carried over.

Before · 02

You repeat yourself constantly

The same preferences, the same context, re-typed into every assistant, every time.

One memory, every tool[2 / 5]

Tell it once. It's there everywhere.

One connected memory centered on you — your notes, preferences, projects, and people — feeding whichever assistant you're using. Continuity and recall across tools, shown not described.

Your personal knowledge — one memory across every toolSIGNATURE
Your personal knowledge — one memory across every tool
shared bucketYouNotesPreferencesProjectsPeopleChatGPTClaude
  • parent
  • subagent
  • peer
  • tool
Accurate and yours[3 / 5]

Stays current · never invents · always yours.

It keeps what's current, only recalls what's grounded, and your data stays yours — private by default, export or delete anytime.

  • Stays current

    When something changes, it keeps what's true now and resolves the contradictions for you.

  • Only what's grounded

    It recalls what you actually told it — no made-up details, no invented history.

  • Always yours

    Private by default. You can see what it remembers, and export or delete anytime.

The simple case of a bigger product[4 / 5]

Start with one assistant. Add more anytime.

This is one assistant using the same governed memory that powers whole teams of agents. When you add a second agent, or a teammate, nothing changes — it's already shared-ready. Same memory, no migration.

What you keep stays private · what you share is already shared-ready
Private to one agent
your assistant

I prefer concise answers and metric units.

your assistant

Draft idea for the trip — still half-baked, keep it to myself.

Shared team memory
SHARED

Project Aurora launches in Q3 — the shared facts everyone works from.

SHARED

Our team writes dates as ISO-8601, in UTC.

Add a second agent or a teammate and it's the same governed memory — what you share is promoted, what you keep stays yours.

RECALL p95sub-200ms

the latency target we hold to — and it works with any model, not just one app

  • RECALL p95sub-200ms
    the latency target we hold to
  • WORKS WITHany model
    OpenAI, Claude, Gemini, open models
  • GROUNDED RECALLheld steady
    our own eval — independent numbers pending

Speed is a maintained SLO, not a guaranteed number. The supporting bars are our own measurements until independent benchmarks land.

Works with any model

  • ChatGPT
  • Claude
  • Gemini
  • Open models
  • MCP

The same product, scaled up: teams of agents working together →

Under the hood[5 / 5]

How one memory connects your tools, and how it scales to teams

The technical depth lives in the developer lane — the SDK + REST, the MCP plugin, and the governance model. See also works with any model and safe & private.

Start free

Give your AI a memory of you.

Tell it once, it remembers everywhere — accurate, private, and yours. Free to start, pay for what you use.