The ask and the milestones behind it are in the deck. Download it, then talk to us.
The position
Private media.
Stripe = payments. Salesforce = customer data. Profila = customer intent.
Profila
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Unavailable The position
Stripe = payments. Salesforce = customer data. Profila = customer intent.
The pitch
The ask and the milestones behind it are in the deck. Download it, then talk to us.
// private_media
Watch customers and they perform. Stop watching and they tell the truth.
Private media is the only place customers can honestly say what they want — and only see results for that want. And when they click, they never fear being retargeted for the months that follow.
// why_now
Both sides are forced to pay.
Brands need a lawful way to reach customers. Labs need lawful human data. Both are compelled — by law, tax and scarcity. No behaviour change required.
The ad rail: Google + Meta took $410B in 2025 — built on watching. The mechanism is being repriced: €7.1B in cumulative GDPR fines, $2.78B to Texas alone, 2–5% digital services tax.
Data licensing: one AI lab paid $1.5B for training on unlicensed data, with 35+ suits behind it. Public human data runs out 2026–2032 (Epoch AI). Every corpus for sale is a stock. Human wants are a flow. Ours renews.
The courts blinked in 2025 — but the direction is one-way, and people, governments and business have stopped defending the watching.
// two_clicks
Two clicks. Two revenue generators.
Click 1 · the ad. We sell ads to brands, priced on privately declared customer intent — CPC · CPV · CPI, never CPM. Google and Meta price inferred attention. They can’t switch — surveillance is their business model.
Click 2 · the verdict. A Yes / No mints a consent-signed intent pair — what she wanted → what she got → confirmed by her. We sell it as AI training data to LLM and physical-AI companies. Annotators are paid to imitate meaning. You can’t annotate honesty.
// the_solution
Four simple steps — private, AI-assisted.
Discover — browse and shortlist brands privately. Nothing follows you.
Signal — AI helps you focus the need or want, in your words.
View — every verdict privately builds the training dataset. No tracking, no cookies.
Match — grade it, good or bad. Brands who join get full, private engagement with their customers.
B2B2C: brands invite their customers; signals are first-party, answered via API or agents. D2C: free private discovery; a vote opens a brand’s door. Pay only on conversion. Zero surveillance. Zero nudging algorithms.
// health
Health. Where private media is the only way in.
A patient connects to a pharmacy privately — voting as “Patient”, sharing no personal information. The pharmacy answers with value, not ads: repeats managed, and a free medication review graded by the patient.
GDPR forbids tracking and ad targeting on health. Next: insurance · legal · banking · careers.
// physical_ai
Physical AI runs the same loop. Intent → action → human verdict.
“Drive gently — my mother gets carsick.” → done → “Yes — but take the corners more slowly next time; she moved around a lot.”
Robots have endless observable data — camera, lidar, telemetry. Nobody has intent + feedback-loop data.
Ads train the model today. The same pairs steer the robots tomorrow. Nobody can scrape “gently.”
// why_us
You can’t bolt private onto surveillance.
Consent lock — every record is born licensed, consent cryptographically signed in, per purpose.
Neutrality lock — Swiss rail, open protocol: 42-True, Apache 2.0. The protocol is public; the corpus head start and the customer relationship are not.
Ceiling lock — watched humans perform. Honest intent only exists where nothing is watching.
To copy this, Big Tech would have to stop watching. Watching is their business model.
The proof
Every grant, paper and collaboration behind the eight years is published on Research Labs — including 42-True, the open protocol.
Next step