Real operating history
Records generated through normal business operations, not synthetic examples or marketing material.
Turn your data into revenue.
Arbor Brokers helps established companies assess proprietary data assets, position qualified opportunities, and engage relevant AI data buyers through a discreet transaction process.
Why buyers care
AI companies need examples of real work. Most of it is not on the public internet.
Think about support tickets with final resolutions, sales records with outcomes, completed projects, claims, invoices, schedules, reviews, or years of decisions captured in your software.
That history may be commercially useful for AI training and evaluation. Arbor helps determine which data opportunities are credible, properly scoped, and ready for buyer consideration.
How the process worksOperational records to qualified data opportunity
Access, scope, privacy, and permitted use are defined before diligence advances.
What we’re looking for
Companies with operating history, proprietary workflows, and records buyers cannot easily source elsewhere.
Repeatable workflows
Systems that capture similar work across projects, accounts, matters, transactions, or service lines.
Decisions and outcomes
Qualified opportunities usually include context, judgment, exceptions, and final outcomes.
Data value estimate
What could your company’s data be worth?
- 1Company
- 2Data
- 3Estimate & call
Industries of interest
If your company works in one of these areas, we should talk.
Software & Technology
Financial, Legal & Insurance
Healthcare & Science
Industrial, Energy & Logistics
Public, Services & Consumer
Common data sources
Does your company use any of these?
You do not need a special data warehouse. Potentially valuable records often live in the systems your team already uses for sales, support, projects, finance, and day-to-day operations.
What counts as data?
Usually, it is the operational record of how work actually gets done.
Databases & exports
Tables, logs, transaction records, and exports from the systems you already run.
Tickets & projects
Support cases, project histories, tasks, issue trackers, and completed work.
Email & messages
Approved communications that show how people made decisions or solved problems.
Documents
Reports, contracts, presentations, spreadsheets, manuals, and internal notes.
Business software
CRM, ERP, billing, support, scheduling, HR, and other systems of record.
Final results
Approvals, resolutions, completed orders, closed deals, and other known outcomes.
Privacy and control
Privacy and control are part of the transaction path.
First, the potential scope is narrowed to specific systems, record types, time periods, and exclusions.
Sensitive information is handled through appropriate privacy, security, and de-identification processes before any transaction. Buyer access and permitted use are controlled by the agreed terms.
- Defined source systems and record types
- Specific exclusions for sensitive information
- Privacy and de-identification review
- Controlled diligence process
- Written permitted-use terms
- Ability to begin with a limited sample
Before diligence advances
The boundaries are written down first.
Sources are defined.
- Approved systems, record types, and date ranges
- Clear exclusions for sensitive projects or accounts
- Limited samples where appropriate
Privacy is addressed.
- Appropriate de-identification processes
- Review of sensitive fields and context
- Company approval before diligence advances
Diligence is controlled.
- Access path agreed before review
- Security expectations established in advance
- No open-ended access to business systems
Use is governed by terms.
- Permitted use, retention, and economics in writing
- No public release of proprietary source records
- Anything outside the agreement stays out
The process
A polished path from evaluation to transaction.
Evaluate
We learn about the business, its workflows, and the types of proprietary operational data it has accumulated.
Scope
We determine which datasets or workflows may be commercially relevant.
Position
We prepare the opportunity for relevant buyers and establish the appropriate transaction path.
Diligence
Qualified buyers evaluate the opportunity, including quality, rights, privacy, and technical requirements.
Close
If terms align, Arbor helps coordinate the transaction through completion.
FAQ
Why would an AI company buy our data?
AI systems need examples of how people do real jobs. A completed support case, reviewed contract, closed sale, or finished project contains decisions and outcomes that are hard to source publicly.
Who are the buyers?
Potential buyers include AI companies, model developers, research teams, and data partners seeking specialized proprietary data. Arbor helps identify relevant demand and coordinate qualified diligence.
What kind of data qualifies?
Useful data usually has real inputs, decisions, and final outcomes. Support histories, claims, completed projects, transaction records, sales pipelines, invoices, schedules, and reviewed documents are common examples.
Do we have to share an entire workspace?
No. A potential opportunity can begin with one clearly bounded workflow, a small date range, or a specific record type. The scope only expands if there is mutual agreement.
How do you handle private information?
Sensitive information is handled through appropriate privacy, security, and de-identification processes before any transaction. The exact approach depends on the data, buyer requirements, and agreed terms.
How much work is this for our team?
The first step is a short call. If there is a fit, Arbor helps define the opportunity, coordinate next steps, and keep diligence focused.
How is the estimate calculated?
The calculator weighs company size, years in business, revenue, number of relevant systems, record history, and how often new data is created. Final economics depend on quality, rights, permitted use, exclusivity, and buyer demand.
Can this become recurring revenue?
Potentially. Some data opportunities may support periodic updates, but recurring economics are determined deal by deal.
What happens on the first call?
We ask what your company does, which systems you use, and what kinds of records you have. You do not need to send us any data for that conversation.
Start a conversation
Turn your data into revenue.
We will discuss your company, the workflows behind the data, and whether the opportunity is worth preparing for buyer consideration. You do not need to prepare or send any data before the call.
Data partnership introwith Ammar · Arbor Brokers
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