Data Capital
Your data is worth more than you think.
Protect it first. Then put it to work, on your terms.
Two stages
Protect first. Then assess the opportunity.
Your business data already reaches AI assistants, meeting recorders, and features inside the software you use. The terms behind those tools vary, and few businesses hold one list of where the data goes.
The same records describe how work in your field is done. That gives them value, first to your own AI work and possibly to others. Before any use, you need to know what you hold and what you may do with it.
So the order is fixed. Protection and rights come first. Assessment and packaging come second, and only for the assets you choose.
The path
The path from exposure to value
Five steps, each scoped before it begins. You can end the work between any two of them.
- Exposure reviewA free 15-minute call on the tools in use, the data involved, and any requests you have received.
- ReadinessData Protection & Readiness maps data flows, rights, consent, and permitted uses.
- Value assessmentDocument the assets with clear rights, the forms they could take, and the buyer types.
- Owner approvalYour named owner approves what may be packaged, for which buyer types, and on what terms.
- License or productData & AI Monetization packages and places only what you approved.
Protection first
Readiness is a fixed price, scoped after the free review. Contract language and an AI-use policy are drafted for your counsel, who keeps the legal judgment.
The approval point
The green step is where your owner decides. Anything without clear rights, or anything you mark private, stays out whatever its potential value.
Packaging and placement
Packaging and placement carry a fixed fee, with an optional revenue share where it fits. We document buyer types and proposed terms, and never promise a buyer or a price.
What you receive
Each stage ends with something you keep.
Both stages produce documents your team can use whether or not anything is ever licensed.
Data Protection & Readiness
- Each AI data flow recorded with its owner and the vendor’s terms.
- Agreed setting changes, made with your IT lead and confirmed.
- A rights map showing what is owned, restricted, or needs permission.
- Contract language and a plain-language AI-use policy drafted for counsel.
- A prioritized plan, with an owner and next action for each finding.
Data & AI Monetization
- An inventory of rights-cleared assets and the forms each could take.
- Documented structure, quality, freshness, and provenance.
- De-identification checked on samples before anything goes for approval.
- Proposed license scope and buyer types for your review.
- A recorded approval from your named owner for every package and term.
From your side, the work needs a sponsor who can approve changes, access to the accounts in scope, and counsel to review drafted language. Most of it runs from settings, agreements, and short interviews rather than your records.
Check your exposure
Start with ten questions about the AI tools and data practices in your business. Your answers stay in your browser, and the full 30-item checklist goes further.
What you already hold
Most businesses hold more than one kind of asset.
These four categories cover most of what a value assessment reviews. Each one is useful to your own AI work before anyone else sees it.
Operational records
Transactions, orders, schedules, and workflow outcomes kept in the systems you run every day.
Decision and correction histories
The approvals, rejections, and corrections your experts made, often with the reason recorded beside them.
Documents and expertise
Procedures, templates, reviewed drafts, and the working knowledge your senior people have written down.
Evaluation material
Labeled examples and checked outcomes that show what a correct answer looks like in your field.
Rights, quality, provenance, and uniqueness decide which of these could be offered. See the full framework of categories, buyer types, and value drivers.
Use cases by industry
Where the path fits.
Typical applications across industries. They show where the work applies, not past client work or results.
- Accounting firm
Answering a vendor’s request for historical data
The exposure review lists the tools that receive client financial records. Readiness then maps which records the firm owns and which need client permission. The partners answer the request from that map.
- Law firm
Confidentiality before any proposed use
Matter documents and client communications are traced against engagement letters and confidentiality duties. Restricted material stays out of scope. Counsel keeps the legal judgment, and the managing partner approves each change.
- Medical billing
Correction histories as evaluation data
Coding and claim-correction decisions, each with its documented reason, can help teams evaluate AI models. Where contracts and consent allow, they are de-identified first. Leadership approves the package and every term.
- Manufacturer
Inspection images with their decisions
Labeled inspection images and accept-or-reject decisions are reviewed against customer restrictions. Customer part designs stay excluded. The operations owner approves any proposed license and buyer type.
- Agriculture producer
Field records with documented provenance
Seasons of planting, input, and harvest records are documented for structure, quality, and freshness. The owner decides which records stay private, such as those tied to supply contracts.
- Nonprofit
Donor and program data kept for its own use
The readiness inventory shows which records donor consent and grant terms cover. The executive director can use it to plan the organization’s own AI work, with nothing offered to others.
Related services
Know your rules and your records.
Data earns value when the rules applied to it and the systems that hold it are clear. Both services make readiness easier to reach and to keep.
The rule asks a business to know what it holds before deciding what to do with it. The data value path puts that into practice, with protection and your approval at its center.
Questions
Will you sell our data?
Nothing is shared, licensed, or sold without your explicit approval of each package and each term. We begin with rights and confidentiality. You may decline at any stage and keep everything private.
Who keeps ownership?
Your records stay in your systems, and any package works from approved copies. A license grants a buyer defined uses on terms you approve. Full engagement terms are finalized in a Master Services Agreement.
What about client confidentiality?
Client agreements and permitted uses are part of the rights review. Restricted information stays outside any proposed package. Where your contracts require client permission, the asset waits until that permission exists.
Is this only for large companies?
No. We work with businesses under 500 employees. A focused, well-documented dataset can justify assessment regardless of company size.
Do we have to license anything?
No. Many reasons to start here have nothing to do with licensing. Knowing where your data goes, and what you may do with it, also supports your own AI work.
Can you tell us what our data is worth?
Not as a figure. A value assessment documents 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 or a named buyer.
How are the services priced?
The data exposure review is free and takes 15 minutes, and Data Protection & Readiness is a fixed price scoped after it. Data & AI Monetization is a fixed fee for packaging and placement, with an optional revenue share. Full engagement terms are finalized in a Master Services Agreement.
Who approves each step?
A named owner in your business. Your counsel reviews drafted contract language and license wording. Nothing moves to the next step without that approval.