EMPORIONem-POR-ee-on
Data & AI Monetization
An emporion was a Greek port of trade, where goods met new markets on agreed terms. Emporion brings your data and AI to market, on your terms.
A path to new revenue from the data and AI you already own.
Is this for you?
- Businesses with years of unique, well-kept data
- Firms whose experts make decisions others would learn from
- Companies with large private codebases
The situation
Something you already own may be worth licensing.
Years of records, expert decisions, and private code describe how work in your field is done. Teams that train AI models and agents look for that kind of material.
Requests can arrive before a business has decided whether to share anything. The questions come quickly: what do we own, what may we share, and on what terms?
You want a clear view of what could be offered and how it would be packaged. Rights, consent, and privacy come first, and nothing is shared without your approval.
Our approach
Rights first. Packaging second. Your approval throughout.
Nothing moves until rights, consent, and privacy are cleared, usually through Data Protection & Readiness. Anything without clear rights stays outside the package.
We then match what you hold to the forms that are licensed: de-identified data, coding tasks, agent training environments, models, and agents. Each package has a defined use, a buyer type, and documented provenance.
Packaging and placement carry a fixed fee, with an optional revenue share where it fits. We never promise a revenue figure or a named buyer, and you approve every term before anything is shared.
Use cases by industry
Where this service fits.
Typical applications across industries. They show where the service applies, not past client work or results.
- Software company
Verifiable coding tasks from resolved defects
After the rights review, resolved defects in repositories the company owns outright become coding tasks for teams that train and evaluate agents. Each task has a starting state, a description, and tests that check the fix, with secrets and client identifiers removed. The company’s owner reviews the removal checks and approves each package and its license scope before placement.
- Medical billing
De-identified coding decisions as evaluation data
Billing specialists make coding and claim-correction decisions that teams evaluating AI models could learn from, each with a documented reason. Where contracts and consent allow, the decisions are de-identified and documented with their provenance, and anything without clear rights stays out. Company leadership approves the package, the buyer types, and every proposed term before anything is shared.
- Agriculture producer
Field records packaged with documented provenance
Years of planting, input, and harvest records describe how crops respond across seasons, soils, and fields. We document their structure, quality, and freshness, and propose a license scope for teams building agronomy and forecasting models. The owner decides which records stay private, such as those tied to supply contracts, and approves each term before placement.
- Manufacturer
Inspection images and quality decisions
Quality teams hold labeled inspection images and the accept-or-reject decisions inspectors made on them. Once rights and customer restrictions are mapped, the approved set is packaged with its labeling rules and provenance for teams training vision models. Customer part designs and identifiers stay excluded, and the operations owner approves every proposed license and buyer type.
- Real estate brokerage
Licensing an accepted transaction checklist agent
A brokerage runs a governed agent that prepares transaction checklists from contracts and disclosures, and staff approve each one before it goes to clients. With accepted results on its own work, the agent can be packaged for other brokerages with its approval points in place. The broker-owner approves the license terms, the buyer types, and any revenue share before placement.
- Construction
Estimating judgment as a training environment
Estimators make judgment calls on takeoffs, allowances, and subcontractor bids that documents alone rarely capture. A simulation of the estimating workflow, built only from rights-cleared project records, can become a training environment for teams that train agents. Client drawings and pricing stay excluded unless contracts allow, and the owner approves the package and each term.
- Energy services
Equipment readings paired with technician diagnoses
Service records pair equipment readings with the diagnoses technicians made in the field and the repairs that followed. Where customer contracts allow, these are de-identified and packaged with documentation of their sources, collection methods, and known gaps. A named owner approves the package, the license scope, the buyer types, and any revenue-share arrangement before placement.
- Education provider
Graded assessments as evaluation sets
Course assessments with rubrics and instructor grades can help teams evaluate how AI models reason within a subject. Learner consent and privacy decisions come first, learner identities are removed before packaging, and the removal is checked on samples. The provider’s director approves which courses are offered, the buyer types, and the terms of each license.
What you receive
Licensed data
De-identified, documented datasets and expert decisions, packaged for AI companies that license training and evaluation data.
Coding tasks and training environments
Verifiable tasks built from your repositories, and simulations of your workflows, for teams that train agents.
Licensed models and agents
Your trained model, or an agent with accepted results, offered to others in your industry.
Rights first
Nothing goes to market until Thesauros has cleared rights, consent, and privacy. We never promise a revenue figure.
How it works
- Review rightsEstablish ownership, confidentiality, and permitted uses.
- Inventory assetsDescribe the structure, quality, freshness, and provenance.
- Assess buyer typesMatch potential uses to the documented asset.
- Design the packageDefine the proposed product or license scope.
- Approve the termsYou approve the package and any proposed sharing before it proceeds.
How success is measured
The measures your approver signs.
Each measure goes into the acceptance criteria with its test data, threshold, and the person who checks it.
- Rights cleared per asset
- Each asset in a package traces to a documented right to use and share it. Assets without clear rights are listed as excluded.
- De-identification checked
- Personal and client identifiers are removed according to the privacy decisions. The removal is verified on samples before the package goes for approval.
- Provenance documented
- Each package records where its contents came from, when they were collected, and how they were processed. Any item can be traced to its source record.
- Fit for its stated use
- Whether the package works for the use it is offered for, such as coding tasks whose tests run and check the result. It is checked before the package goes for approval.
- Terms approved before sharing
- Every package, license scope, and placement has a recorded approval from your named owner. The approval record is checked before anything is shared.
Where care is needed
What we watch, and how it is handled.
- Rights before value
- An asset’s potential value never moves it ahead of the rights review. We package only what your rights, consent, and privacy decisions allow.
- Combined records
- Records combined together can reveal more than any one of them. We check de-identified packages for combinations that could point back to a person or client, and remove fields until your privacy decisions are met.
- Assets that show how you win work
- Some assets reveal pricing, methods, or client relationships. We flag those for your decision, and anything you mark private stays out whatever its potential value.
- Expectations on revenue
- Prices are set in the market, and buyer interest varies by asset. We document buyer types and proposed terms, and never promise a revenue figure or a named buyer.
- Use after licensing
- License terms set what a buyer may do with each asset. We propose scope, use limits, and provenance terms for your review, and your counsel approves the final wording.
Who does what
Your team decides. We engineer.
Your team
- Complete, or confirm, the rights, consent, and privacy review
- Name an owner who approves every package and every term
- Give access to the data, code, models, or agents in scope
- Decide which assets stay private, whatever their potential value
- Approve or decline each proposed license
Sophrono
- Match your assets to the forms that are licensed
- Document structure, quality, freshness, and provenance
- De-identify and package the approved assets
- Propose license scope and buyer types for your review
- Place approved packages under the terms you set
At the end
The decisions you make next.
The service ends with evidence and a choice. Each option is yours, and none is assumed.
License the approved package
Approve placement under the terms you set. Each license decision stays with you, and you may decline any proposed buyer type.
Keep it private
Decline at any stage, and keep the documentation for your own AI work. Model Training & Fine-Tuning can build a model on the same records.
Clear more rights first
Where valuable assets lack clear rights, Data Protection & Readiness maps the consent and permissions needed before packaging.
Build a product first
If a model or agent would serve buyers better than raw data, build and accept it on your own work first. Model Training & Fine-Tuning or Custom Agentic Systems can take that step.
Before we start
What to have ready.
- The findings from Data Protection & Readiness, or your own rights and consent review
- A view of the data, code, models, or agents you would consider offering
- A list of anything that must stay private
- The person who will approve license terms
- Any requests for your data or models you have already received
Related services
What “accepted” means
Measured against criteria you agree to in advance.
- The rights review identifies restrictions and approval owners.
- The inventory documents the assets included and excluded.
- The proposed package has a defined use and buyer type.
- Your owner approves the proposed license or product scope.
Full engagement terms are finalized in a Master Services Agreement.
Request a data value assessment
Tell us about the data you hold.
Protection comes first. We reply with what an assessment would cover for your data.
- A senior engineer reads every request
- A reply by email with the next step
- No obligation until scope and price are agreed
Not ready to scope this? Ask an engineer first: a free 15-minute call that names the agentic systems that could fit.
The Canon rule behind this service
Data & AI Monetization answers to Canon IV.
Free checklist and self-assessment
Where is your data going?
Thirty checks across your AI tools, vendor terms, contracts, and controls, plus a ten-question self-assessment that scores your exposure in two minutes.
- Every place AI tools can reach your data
- Which vendor terms allow retention or training
- The contract clauses and settings that close the gaps
AI Vendor Data Exposure Checklist
Preview it firstWhere this fits
- Learn Data Capital
- Check free Data exposure checklist
- Protect Data Protection & Readiness
- Earn Data & AI Monetization
Not ready yet? Data Protection & Readiness. After this: System-of-Record Architecture or AI Stewardship.
Questions
Who keeps ownership?
Ownership and permitted uses are agreed before any transaction. Full terms are finalized in a Master Services Agreement.
What is excluded?
Information without appropriate rights or required permissions is excluded from the proposed package.
Is revenue sharing available?
A revenue-share structure can be considered where it fits the proposed work. Commercial terms are agreed for the engagement.
Can you tell us what our data is worth?
Not as a figure. We document what you hold, the forms it could take, and the buyer types that license them. Price is set in the market, and we never promise a revenue number.
Do we have to license everything we package?
No. You approve each package and each proposed term, and you may decline at any stage.
How is personal information handled?
It is removed or de-identified before packaging, following the privacy decisions made in the rights review. Anything that cannot be cleared stays out.
Can we license an agent we built with you?
Where you hold the rights and the agent has accepted results, it can be packaged for others in your industry. It ships with its approval points in place, so people still review its consequential actions.
Who licenses these assets?
Teams that train and evaluate AI models and agents, and businesses in your industry that could use a model or agent you built. The proposal names buyer types, never promised buyers, and you approve every placement.
How is the fee structured?
Packaging and placement carry a fixed fee, with an optional revenue share where it fits. Full engagement terms are finalized in a Master Services Agreement.
Do we need Data Protection & Readiness first?
Rights, consent, and privacy must be cleared before packaging, usually through Data Protection & Readiness. If you have completed your own review, we start from its findings.
Do our clients need to agree?
Where your contracts or privacy obligations require permission, yes. The rights review identifies those cases, and any asset without clear permission stays out of the package.
Will buyers see our raw records?
Buyers receive only the approved package, under the terms you set. Identifiers are removed or de-identified before packaging, following the privacy decisions in the rights review.
What makes an asset suitable for licensing?
Assets that are unique, well kept, and clearly owned tend to suit licensing. We document structure, quality, freshness, and provenance so you can judge each one.
Can we license a model we trained?
Where you hold the rights to the model and the data behind it, yes. The model is documented with its provenance and intended use, and you approve every proposed license.
Can a package be refreshed later?
Yes, where the license terms allow it. A refreshed package goes through the same rights check, de-identification, and owner approval as the first.
Does packaging change how we use our own data?
No. Your records stay in your systems, and packaging works from approved copies. The documentation also supports your own AI work.
Can we start with one asset?
Yes. A single package can be scoped, built, and approved on its own. Further assets can follow from the same rights review.