Your company’s data may be worth more than you think.
Years of decisions, expertise, and experience live inside your business. Explore how licensing that knowledge could create a new source of revenue and help build the next generation of AI.
Explore a new source of value through a data partnership with Adzzat Labs. Real operational knowledge, licensed for a clearly defined purpose.
01Your knowledge, a defined license
02Permissions before access
03Context that makes data useful
02 / A considered path to partnership
How a data partnership works.
Talk to our teamFrom the first conversation to an approved licensing package, establish what can be shared, how it will be prepared, and when payment is due.
- 01
Agree the scope
Identify useful records together. Confirm licensing rights, exclusions, permitted uses, and the commercial terms before moving forward.
- 02
Prepare the records
Agree a preparation plan covering sensitive information, de-identification, formatting, and quality review for the proposed use.
- 03
Approve & deliver
Review the proposed package and deliver approved material under the access, confidentiality, and usage terms in the agreement.
- 04
Receive payment
Payment follows the acceptance criteria and milestones set in your agreement. Any future packages are scoped and priced separately.
03 / What useful data looks like
Target industries
You do not need to manufacture a dataset. Start with the knowledge your organization already creates. Explore a few examples below.
Check if you qualifyExamples of potential sources. Suitability depends on ownership, permissions, and the intended use.
Illustrative record / 01
From a problem to a considered decision.
- Context
A team investigates a recurring performance issue.
- Judgment
Engineers compare approaches, constraints, and trade-offs.
- Outcome
A reviewed change records what worked and why.
What a model can learn
Technical reasoning, debugging, and multi-step problem solving.
- Design documents
- Issue histories
- Code reviews
- Product requirements
Illustrative example, not customer data.
Start with the systems your team already uses.
These are examples of potential sources, not requests for unrestricted access. Only records you have the rights to license belong in an agreed package.
- Team conversations
- Slack, Teams, or other internal discussions that show how work moves from question to resolution.
- Email & calendars
- Business correspondence and project coordination, reviewed for permissions and sensitive information.
- Documents & files
- Design briefs, reports, spreadsheets, and knowledge bases with useful context and provenance.
- Business systems
- Approved CRM, support, and operational records that connect a task to a decision and outcome.
04 / Built around trust
Your business.
Your boundaries.
A valuable partnership starts with clarity about what belongs in it, and what does not.
- Ownership & permitted use
- Define the material, duration, and uses covered by the license. Your underlying records remain part of your business.
- Explicit exclusions
- Identify restricted records, third-party material, and sensitive information before agreeing the scope.
- Preparation & provenance
- Agree privacy handling and quality requirements for the specific dataset, with a documented source and preparation process.
05 / Explore the potential
What could your
data be worth?
Adjust your team size, available history, and source coverage to explore an illustrative licensing scenario. A conversation with our team is the next step toward a real assessment.
Illustrative licensing value
USD · one hypothetical licensing package
An illustration of potential scale, not an offer or a prediction. Actual payment depends on the records, rights, quality, buyer demand, and agreed terms.
How this illustration is calculated
Employees × years of usable records × selected source categories ÷ 4 × an assumed $30–$80 per employee-year. Categories have equal weight in this simplified model.
These are demonstration assumptions, not observed market rates or Adzzat pricing. The range is for a single package, not annual recurring revenue. A real assessment may fall outside it, including no eligible value.
Calculated in your browser. No records or contact details required.
When would we be paid?
Payment amounts, acceptance criteria, and timing are agreed before delivery. Any payment follows those contractual milestones. Additional datasets or future updates would need their own agreed scope and commercial terms; recurring revenue is not automatic.
What is an enterprise data partnership?
A scoped arrangement to license business records for agreed AI training or evaluation uses. The conversation starts with the knowledge in your organization, whether you have the rights to license it, and how it might meet a research need.
What kinds of data could be relevant?
Operational records that capture context, decisions, and outcomes: engineering documents, support histories, internal knowledge, and business workflows. A record that explains why a decision was made can be more useful than a large volume of disconnected information.
Do we need to share data to start the conversation?
No. Start with a high-level description of your organization and the types of records you hold. Do not send raw records, personal information, or confidential material through the enquiry form. Any later sample review or access should be agreed separately.
How are sensitive information and permissions handled?
The proposed scope needs an ownership and permissions review, together with explicit exclusions and dataset-specific privacy requirements. Redaction, anonymization, or other preparation depends on the material and intended use. Removing direct identifiers alone does not guarantee that a dataset is anonymous.
What determines the commercial terms?
Relevance to the research task, depth of context, quality, uniqueness, and the rights available all matter. Terms are assessed for each partnership; there is no standard payout or guaranteed valuation. The calculator uses transparent demonstration assumptions and does not quote an actual price.
Can an AI lab request a particular type of data?
Yes. Tell us the domain, capability, or evaluation gap you are working on. We can discuss the data characteristics and expert input the project would need, then explore the fit with potential sources.
A new chapter for your company’s knowledge
You have the experience.
Let’s explore its potential.
Tell us a little about your business and the knowledge it holds. We’ll start with the possibilities.
Explore a partnershipAn initial conversation. No data upload required.
Building models? Discuss your data requirements