Your API calls are now training data you own, a great launch for owning your intelligence stack.

Mubit reads the calls your agents already send to OpenAI or Anthropic, finds the tasks that repeat, and trains small models that you own.

so you pay less and wait less while the big model handles the rest.

> The company says they refresh every few minutes.
> The integration is one line. You swap the base URL and keep the same client code. If you’d rather not touch that, you can connect the traces you already collect.
> I like is the split. Narrow, repeated work moves to a model trained on your own traffic. Anything outside those tasks still goes to the frontier model.

All these means, two companies on Mubit end up with different small models, because each is shaped by its own agents’ work.

Remembering feedback in the prompt is unpredictable. So what Mubit is doing that instead of putting lessons into the prompt, it trains small models on the tasks your agents repeat, so the improvement lives in the weights.
We started Mubit in Aberdeen. No network, no lab, nobody knew us. We just wanted AI systems that actually work.

Today we work with some of the best companies and engineers in the world.

And the thing we kept seeing: you and your competitor run the same AI. It should be yours. the next 48 hours for $100 free credits. Enterprises get the first month free.

Oct 23, 2026 · 6:24 PM UTC

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Replying to @rohanpaul_ai
@rohanpaul_ai what happens with traffic that has customer data in it? if a customer asks to be deleted, can you get them back out of the small model
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Replying to @rohanpaul_ai
@rohanpaul_ai 按这个分工,最值得期待的是那些每天重复、又不值得单独开发的零碎任务,终于有机会用更低的成本处理。
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Replying to @rohanpaul_ai
@rohanpaul_ai 任务一变,小模型的优势会不会很快被吃掉?
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Replying to @rohanpaul_ai
@rohanpaul_ai Me watching AI videos at 2am: "wow this is incredible." Me realizing I've been scrolling for an hour: 😭
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Replying to @rohanpaul_ai
@rohanpaul_ai Automatic task routing down to local SLMs saves massive cloud spend.
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Replying to @rohanpaul_ai
@rohanpaul_ai Repeated tasks are most of what a small bot team actually does, so this is the right idea. My question is how much call volume you need before a small model beats just prompting a frontier one on the same job?
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