The AI That Actually Knows You
Every AI tool asks you to start over. Your communication style, your priorities, your recurring context — you re-explain them every session, to every model. MemoryLake stores who you are once, and loads that context into every AI session you run, regardless of which model you're using.
The Memory Problem
You've explained your role dozens of times. You've described your working style, your preferences for tone, the specific context of your projects. Every time you open a new session — or switch to a different AI tool — you start over. The models are getting smarter. The memory problem isn't getting better.
What MemoryLake Does Differently
Background Memory as your AI identity layer — Store your role, working style, communication preferences, recurring project context, and any constraints that should always apply. Background Memory is read-only for the AI: it shapes every session without you having to prompt it.
Skill Memory for your frameworks and workflows — The thinking frameworks, templates, and processes you've developed aren't generic — they're yours. Store them in Skill Memory and invoke them by name in any session, with any model.
Consistent identity across every model — Whether you're in Claude, ChatGPT, Grok, or Gemini, your Background Memory loads first. Every AI session starts knowing who you are, what you're working on, and how you prefer to work.
How It Works
- Connect — Set up MemoryLake and connect it to the AI tools you use. Takes under ten minutes.
- Structure — Define your Background Memory: role, style, recurring context, constraints. Add Skill Memory for your go-to frameworks and workflows.
- Reuse — Open any connected AI. Your context loads automatically. You spend your session on the work, not the setup.
Before & After
| Without MemoryLake | With MemoryLake | |
|---|---|---|
| Session start | Re-explain role, style, context | Background Memory loads automatically |
| Switching models | Start over with each model | Same identity available everywhere |
| Recurring frameworks | Copy-paste or re-prompt each time | Stored in Skill Memory, invoked by name |
| Preference evolution | Informal, inconsistent | Versioned and auditable |
Built For
Knowledge workers, consultants, researchers, founders, and anyone who uses AI tools as a core part of their work and wants those tools to behave like they actually know them. If you've ever written a long system prompt and wished it could follow you from tool to tool, Background Memory is what you were asking for.
Related use cases
Frequently asked questions
What's the difference between Background Memory and a system prompt?
What's the difference between Background Memory and a system prompt?
A system prompt has to be written fresh for each session and each model. Background Memory is stored once, maintained over time with versioning, and loads automatically into every connected AI session. You maintain one source of truth instead of many copies.
Can I have different preferences for different AI tools?
Can I have different preferences for different AI tools?
Yes. You can configure context that applies globally and context that applies only to specific models. If you use Claude for writing and ChatGPT for analysis, each can have relevant context layered on top of your shared identity.
How does MemoryLake handle preferences that change over time?
How does MemoryLake handle preferences that change over time?
All memory entries are versioned. When your preferences evolve, you update them — MemoryLake records the change and when it was made. You can see how your working style has shifted and roll back to a prior version if something doesn't stick.