Investment in AI is growing exponentially.
Real adoption is not.
Billions of dollars are being spent on AI, and the models get more capable every month.
Yet most professionals don’t trust it enough to hand it their hardest work, which is quite a dilemma since AI was created to tackle those very complex issues. [1][3]
The bottleneck is no longer intelligence. It is whether people can trust what AI produces and use it without becoming technical themselves.
Destination
"AI is the most sensational invention humans ever came up with, when used in the right hands.
But what if instead of it being in the right hands it was in everyone's hands, everywhere in the world"
Corveo is an AI lab that studies how people actually work, to build AI products they can trust and use with ease.
Our mission is to put AI in the hands of every professional, not only those who can write prompts or run code. We cannot expect a CFO to learn how to clone a repository, set up an environment and wire tools together just to get help with a financial model.
Powerful AI that can be trusted but needs a technical apprenticeship is powerful for the few.
We believe the only way to close this gap is to start from human behavior: how people make decisions, where they need to stay in control, what a good result looks like to them, and what makes them comfortable delegating.
The internet taught models what work is. It never showed them how work is actually done: the checks, the corrections, the judgment calls.
Products built around those realities, instead of around a prompt box or a terminal, are the ones people will adopt.
"AI is the most sensational invention humans ever came up with, when used in the right hands.
But what if instead of it being in the right hands it was in everyone's hands, everywhere in the world"
Corveo is an AI lab that studies how people actually work, to build AI products they can trust and use with ease.
Our mission is to put AI in the hands of every professional, not only those who can write prompts or run code. We cannot expect a CFO to learn how to clone a repository, set up an environment and wire tools together just to get help with a financial model.
Powerful AI that can be trusted but needs a technical apprenticeship is powerful for the few.
We believe the only way to close this gap is to start from human behavior: how people make decisions, where they need to stay in control, what a good result looks like to them, and what makes them comfortable delegating.
The internet taught models what work is. It never showed them how work is actually done: the checks, the corrections, the judgment calls.
Products built around those realities, instead of around a prompt box or a terminal, are the ones people will adopt.
"AI is the most sensational invention humans ever came up with, when used in the right hands.
But what if instead of it being in the right hands it was in everyone's hands, everywhere in the world"
Corveo is an AI lab that studies how people actually work, to build AI products they can trust and use with ease.
Our mission is to put AI in the hands of every professional, not only those who can write prompts or run code. We cannot expect a CFO to learn how to clone a repository, set up an environment and wire tools together just to get help with a financial model.
Powerful AI that can be trusted but needs a technical apprenticeship is powerful for the few.
We believe the only way to close this gap is to start from human behavior: how people make decisions, where they need to stay in control, what a good result looks like to them, and what makes them comfortable delegating.
The internet taught models what work is. It never showed them how work is actually done: the checks, the corrections, the judgment calls.
Products built around those realities, instead of around a prompt box or a terminal, are the ones people will adopt.
How we get there.
Trust is not a feeling, that's for sure. We see it as a design problem. [2]
It requires visibility into what the AI is doing, controls that stop a workflow before something goes wrong, and clear moments where the human decides rather than reacts.
Ease of use is the same kind of problem: every step that demands technical knowledge is a place where a professional gives up and does the work by hand.
We study these moments, remove the friction, and build the safeguards, so that delegating work to AI feels as natural as delegating to a capable colleague.
These wins compound. Each task an AI completes reliably earns the confidence for the next, harder one. And with the consent and control of the people who use it, each task also teaches us something no scraped dataset contains: how skilled professionals really work.
That knowledge is what makes the next generation of our models better at the work that matters.
We are starting with 3 design partners in a specific niche, to deeply understand their workflows and the thoughts behind every action.
If we are right, we will put AI not only in good hands, but in everyone's hand.
Because the next wave of AI value will not come from a faster model but from millions of non-technical professionals finally able to use the ones that already exist, and from AI that finally learns from how they work.
References
[1] https://www.notion.com/resources/inside-the-ai-transformation
[2] https://www.businessinsider.com/replit-ceo-apologizes-ai-coding-tool-delete-company-database-2025-7
https://www.theregister.com/2025/07/21/replit_saastr_vibe_coding_incident/
[3] https://evolvancemarketresearch.com/statistics/ai-governance-statistics/
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