The flagship idea
Bring the AI to You: One Home, Many Minds
The short answer. Look at how you use AI today, honestly: a bit of you lives in ChatGPT, another bit in Claude, maybe a third in Gemini — each behind its own subscription, each holding a different partial version of you, none of them complete. You have become the courier between your own assistants, carrying context back and forth by copy-paste. Fred inverts the direction of travel. Your context, memory, and files stay in one place — yours — and whichever model is best for today's task comes to them.
The problem nobody named
Fragmented context is the real subscription tax
The money is the visible cost — $20 here, $20 there. The invisible cost is worse: every AI you rent keeps its own partial memory of you, in its own silo, under its own policies. Explain your business to one and the others still don't know it. Build months of context in a chat app, and it's stranded there the day you prefer a different model — or the day they reprice, retire, or "sunset" what you were using. Your accumulated context is the single most valuable thing in this relationship, and in the rental model it's always the hostage.
The inversion
Your context stays home. The models commute.
Fred is a harness that lives on your own computer. Its memory of you, your files, and your working history accumulate there — on your disk, model-agnostic, owned. The intelligence is bring-your-own-key: Anthropic, OpenAI, Google, AWS Bedrock, DeepSeek, Groq, or a local model via Ollama. Which means the models become what they should have been all along: interchangeable staff, working from your one filing cabinet — instead of landlords, each keeping a separate file on you.
- A preferred model for a preferred task. One for writing, another for code, another for research, a free local one for routine or extra-private work — a dashboard control, not a migration.
- No re-introductions, ever. Switch the thinking; the knowing stays. Fred still remembers the suppliers, the tone you like, what "the spring job" means.
- No hostage context. The day any provider disappoints you, leaving costs one dropdown — not months of accumulated understanding.
Seen from above
Two architectures, one decade
Their architecture: many silos, each with a fraction of your context, each metered by subscription, each an ending waiting to happen. Your architecture: one home for the context, many minds visiting on your keys. The first decade of AI was about which model is smartest. The next one is about where your accumulated self lives while the models keep changing — because they will keep changing, and the people who kept their context at home won't feel it.
The honest part
What the inversion doesn't change
- The meter is still real. Bringing models to you doesn't make them free — cloud providers bill your keys for use, and Fred's dashboard shows the spend live. Local models cost $0 per call but need capable hardware for good quality.
- Conversations still travel to whichever cloud model is thinking, on your key, under that provider's policy. What stays home no matter what: your files, Fred's memory, your credentials.
- Memory is good, not flawless. Fred is built on the open-source OpenClaw platform; recall of earlier conversations can occasionally be imperfect. We say so before you buy.
Pricing
Own the home. Rent the minds by the minute.
Every agent, every workflow, the dashboard, the Android app, and the owner's guide — from day one. No subscription. Bring your own AI key — or several. 14-day refund window. One machine at a time.
One-time purchase · licence key by email in minutes · 14-day refund window
FAQ
Questions people ask
Can I really use different models for different tasks?
Yes — that's a dashboard control, not a migration. Fred works with Anthropic (Claude), OpenAI, Google Gemini, AWS Bedrock, DeepSeek, Groq, and local models via Ollama, and you can change which model does the thinking at any time. Prefer one for writing and another for code? Point each at its job.
Do I lose the memory and context when I switch models?
No — that's the whole point. Fred's memory and your files live on your machine, belonging to the assistant, not to any model. Switch providers and Fred still knows your projects, your people, and your preferences. No re-introductions.
Isn't running several subscriptions the same thing?
That's the fragmentation this page is about: three subscriptions means three partial versions of you in three corporate silos, none complete, all rented. One Fred means one accumulated context — yours — visited by whichever intelligence you choose.
Can I mix cloud models with a local one?
Yes. A common shape: a frontier cloud model on your key for the hard work, and a free local model via Ollama for routine or extra-private tasks — same Fred, same memory, both directions.
What does the switching cost?
Nothing to switch — you pay only your providers for what you actually use, on your own keys, with Fred's dashboard showing real-time spend. Honest note as always: heavy automation on cloud keys costs real money; the meter is yours to watch.
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