Your company's data is valuable to AI

AI systems learn from what is public. What they lack is how companies actually work: procedures, customer conversations, quotes, technical reports. AI labs pay companies that agree to license this data, anonymized and under contract. You keep ownership: you grant a limited license, at no cost to you.

What AI labs are looking for

• written internal procedures: SOPs, checklists, quality controls;
• customer conversations: requests, replies, support tickets;
• business documents: quotes, estimates, service or inspection reports;
• history: several years of records are worth more than a single year;
• documents from specialized trades, where public examples are scarce.

How it works

1. You describe your company and the data it holds, in two minutes.
2. We review your file and get back to you to complete it.
3. A buyer makes you a priced offer. We tell you its name before passing on anything.
4. Nothing is extracted before a signed contract. It sets the scope, the price and the anonymization rules.
5. The data is anonymized before delivery: neither your customers nor your employees can be identified.
6. You get paid as set in the contract.

What does not change

Your business carries on, your customers stay yours, and nothing is licensed without your signature. You are not selling your company: you license an anonymized copy of its records.

What you keep, what you grant

Trust framework: model contract, anonymization standard, consent (in French)

Is your company interested?

Two minutes. No commitment, and nothing is passed on without your consent.

1. The company

Company name *

Website

Country *
United StatesCanadaUnited KingdomIrelandAustraliaSwitzerlandEuropean Union (other)Other

Industry *
IT and digital servicesStaffing and recruitingFinancial services (excluding client files under secrecy)Consulting and professional servicesTransportation and logisticsConstruction and skilled tradesEngineering, surveying, architectureReal estate (management, brokerage, development)Retail and salesManufacturingMarketing and communicationsHospitality and food serviceEducation and trainingOther

Number of employees *
1 to 910 to 2930 to 200more than 200

Years in business
less than 33 to 1010 to 25more than 25

Company status *
activewinding down voluntarilyin liquidationin bankruptcy

Your role *
founder or executivepartner or shareholderliquidatorbankruptcy trusteeother

First name

Last name *

Work email *

Phone

Continue

2. Its data

Types of data available

procedures and SOPs internal documentation or knowledge base templates and frameworks project management (tasks, tickets, histories) internal communications (Teams, Slack, email) emails with customers support tickets or requests quotes and invoices technical or inspection reports CRM or tracking files call recordings other

Tools used (Microsoft 365, Google Workspace, name of your CRM or ERP…)

Years of history available
less than 22 to 55 to 10more than 10

Language of the data

English Spanish French German other

Do you accept anonymization before licensing?
yesto be discussed

Preferred timing
as soon as possiblewithin 3 monthsin 6 months or later

Details (optional)

I would like to receive the full model contract (version 0.1).

I agree that the information in this form may be passed on to the data buyers Registres works with, so that they can make me an offer. The name of each buyer will be given to me before anything is passed on. Form hosting: Formspree (United States). Retention: 12 months after the last exchange. *

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What we do not accept

Data covered by professional secrecy (attorneys, notaries, accountants for their clients' files, healthcare professions), health data, and any data the company has no right to license.

Registres is a gateway between data and AI systems, with two pillars: public data published by governments, which we make readable by AI agents with its license and provenance; and company data, which we connect with the AI labs that buy it, only with its owner's consent. The common thread: you always know where a piece of data comes from and who consented to its reuse.

Further reading

• Trust framework: model contract, anonymization, consent (in French)
• Transparency: our partners and how we are paid (in French)