Our manifesto
Building the Network of Expert Knowledge.
The world is drowning in data, and still the most valuable thing in any decision is the judgment of someone who has done it before. That knowledge is not public. It is not indexed. No language model can generate it. It lives in the minds of experienced professionals, and most of it never leaves.
We are changing that. dilmind gives experts a new way to share what they know, to protect it, to amplify it and to earn from it, and gives decision makers the insight they need to decide better, and faster.
I. The knowledge that matters most is not written anywhere.
Years in an industry leave something no report can hold: a feel for the market, a sense of who is about to move, the detail only an insider notices, the judgment to tell a good deal from a bad one. It is the layer behind every important call. It is live, it is contextual, it is built on judgment. It does not live in any model, and it will not for some time.
And it never stands still. A market turns in a quarter, a technology in a year, a deal in a week. What an operator knew last spring is already being rewritten by what they see today. Knowledge like this cannot be captured once and filed away. It has to be shared again and again, by the people living it.
That only happens when sharing is worth it. Experts need a reason to share, the tools to make it easy and the safeguards to make it safe: an incentive layer and an infrastructure layer, built for expertise that keeps moving. That is what we are building.
II. The old model treats experts as a supply.
For decades, the people who know have been handled like inventory: a name in a database, a one-hour call, a survey to fill in, a fee, then silence. Their knowledge was used once and forgotten, or used again without them.
The call itself was never neutral. One expert, one client, one hour, and a conversation that drifts toward what the person paying wants to hear. Consensus passes for insight, and the uncomfortable view stays unsaid.
Nothing in it gave experts a reason to share more: no reward beyond the hour, no say over where their words went, no protection once they were spoken.
Now a new buyer has arrived: AI labs. They are hiring experts by the thousand to teach their models the job itself: how an analyst builds a case, how an engineer traces a fault, how a buyer runs a tender. The expert is paid by the hour to train the system built to replace them. They sell their expertise once, and lose their place for good.
III. We refuse that bargain.
Expertise has become raw material, and for good reason. The data that matters now is the data you will not find in the public domain: what the people inside a market know, and what lets one decision maker see what others miss. It is the difference between a good decision and a costly one.
But not all expert data is the same. One kind is knowledge of a market: how an industry works, where a company stands, how a value chain is shifting, a judgment on what comes next. It informs decisions; it does not teach a machine to do anyone's job. The other kind is the know-how of the job itself, how a task is done, step by step. Sell that to an AI lab and the model learns to do the work. The expert loses more than a job: out of the industry, they stop learning what only working in it can teach, and the knowledge everyone relied on stops growing.
We take the opposite side. We share the first kind, with the expert's consent and the expert paid every time it is used. dilmind does not feed AI labs, does not train models on what experts tell us, and never will.
Your words are never used, and never sold, to train AI.
We work for experts.
We are building the infrastructure layer for expert knowledge: the incentives, the tools and the safeguards that make sharing worth it.
Share.
An AI interviewer leads a voice conversation of about 20 minutes about work they have actually done. No scheduling, no time zones, in their mother tongue, with follow-up questions that feel like talking to a peer, not filling in a form.
Protect.
Their name or anonymous, their choice, interview by interview. Every interview screened for confidential details before it reaches anyone. And never handed to an AI lab.
Amplify.
Each interview opens what their peers said on the same topic. Their digital mind carries what they know further, answering questions day and night, and makes their expertise easier to find.
Earn.
€100 per substantive interview, then royalties each time a client uses it, through the library or their digital mind. Knowledge that keeps working keeps paying.
IV. Augment the expert. Never replace them.
The more machines write, the more trusted human expertise is worth. We use AI for one thing: to make that expertise easier to share, easier to reach and possible to scale, without ever taking the expert out of it.
A digital mind, always on.
Once an expert has shared, their knowledge stays within reach through their digital mind: any hour, anywhere, without waiting for their calendar. People ask follow-up questions and get answers drawn from what the expert said, and only that, always labelled as generated by AI. For the expert, it is a living profile that grows with every interview.
Candid by design.
Our AI interviewer puts the same questions to every expert, with no client in the room and nobody to please. The answers are what experts actually think, and they can be read side by side.
Compliant by process.
Every topic is checked before it is asked, so no question invites a breach of confidence. Every interview is screened when it ends, and any confidential passage is taken out before a word reaches the library.
V. Better questions. Faster decisions.
The future of knowledge is not more information. Decision makers already have more than they can read. It is about asking better questions, and putting them to the people who can answer.
That is how we work. Our research, run with AI, maps a market, finds where the evidence runs out, and turns each gap into questions for the experts who have lived it. Desk research where the data is enough; human judgment where it is not.
And decisions are made faster every year. The insight behind them has to keep up: not weeks of calls, but answers in days, and a digital mind ready the moment a question comes up.
Better for experts is better for decisions. Experts who are respected, paid and protected give their best, and that is what decision makers come for.
VI. Not respondents. Members.
An expert is not a one-time survey respondent, nor the provider of a single engagement. They are a long-term member of a network, and their value compounds. Every interview confirms what they know. Every one enriches their profile, records what they agree to share and how, learns what they prefer, and builds trust, on both sides.
Every interaction should strengthen that relationship, not simply complete a transaction. That is the difference between a database and a network.
VII. What we commit to.
- We pay for every substantive interview, and again each time it is used.
- We show an expert's name only where they chose to show it.
- We never rank an anonymous interview below a named one.
- We put the same questions to every expert, with no client in the room.
- We screen every interview for confidential details before it reaches anyone.
- We build for the long run: one relationship, many conversations.
- Your words are never used, and never sold, to train AI.
Empowering Experts. Elevating Knowledge.
This is the network we are building. Take your place in it.