How it works
How an expert's judgment becomes an AI model, and how we keep it faithful, owned and worth trusting.
What an Asyncwork model actually is
It is not a chatbot with a personality setting, and it is not the whole internet with a friendly voice. An Asyncwork model is a Small Language Model trained on one expert’s methodology and nothing else: their frameworks, their case patterns, the judgment they have built over a career. It answers the way that one specialist would, because that is the only thing it has learned.
How it learns to think like the expert
Capturing judgment is a loop, not a download. The expert talks through how they work, and our AI interviewer draws out the reasoning behind their decisions. The model drafts answers. The expert reviews and corrects them, and the model sharpens with each round. We call this referential learning. It is how decades of hard-won instinct become something a model can carry, without flattening it into a script.
How we keep it faithful
A model is only worth building if it stays true to the expert. So it is measured against their own standard, not a generic benchmark, and the expert stays in the loop to catch drift. The foundational work runs on the model. The high-stakes calls still go to the human. One team of FBI and CIA-trained deception specialists put their model in front of FBI-trained peers and had it assessed live before they trusted it with their name.
How ownership is actually enforced
Ownership here is built into the architecture, not just the marketing. Your model is trained in isolation, so your work never trains another advisor’s model or any platform model. The weights, the data and the configuration are yours, and you can export them and walk whenever you want. It is the same promise written into the advisor agreement: what you build stays yours.
Curious where you fit? Find an expert or build a model of your own.
Talk to us
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