Memory Sync

Portable AI memory sync across assistants

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Inspiration

AI assistants are getting better, but memory is still trapped inside closed platforms. If you teach ChatGPT your preferences, project context, and working style, that context usually does not move cleanly to Claude, Gemini, or the next tool you want to use.

Memory Sync was built to make that memory portable instead of platform-bound.

What it does

Memory Sync is a Chrome extension that helps users sync memory across ChatGPT, Claude, Gemini, Grok, Kimi, Mistral, and Copilot.

It keeps one editable Memory.md as the source of truth, so users can pull memory out of one assistant, review and refine it, then push it into another assistant without starting from zero each time.

How we built it

We built Memory Sync around a simple Pull, Edit, Push workflow:

  • Pull long-term context from an assistant
  • Edit and curate that context in Memory.md
  • Push the same memory into another assistant

The current version focuses on a human-in-the-loop workflow. The extension handles navigation, prompt injection, sync state, and memory-file management, while the user stays in control of what gets kept and what gets sent.

Challenges we ran into

The hardest part was not flashy AI UX. It was designing a workflow that stays useful across multiple platforms with different interfaces, behaviors, and memory models.

Another challenge was keeping the system honest. We did not want to pretend memory portability was fully automatic when review and editing are still important. That is why the product keeps Memory.md visible and editable instead of hiding memory behind a black box.

What we learned

We learned that long-term AI memory is most valuable when users can actually inspect, rewrite, trim, and move it.

The real problem is not whether one assistant can remember more. The real problem is whether your memory remains portable, editable, and under your control as you switch models.

What's next for Memory Sync

Next, we want to deepen automation while keeping the workflow transparent, trustworthy, and user-controlled. The goal is simple: switching models should not mean re-explaining who you are every time.

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