What to check when data is offered to multiple AI labs

When you receive offers from several AI labs for the same operational data, first verify the ownership rights, the de-identification process, and the scope of the license. Only after those three points line up should you move forward with any agreement.

Core items to verify

A consistent checklist helps you compare proposals quickly and spot hidden differences.

• Ownership and permission. Confirm that your company holds clear title to the data and that any customer contracts allow a de-identified license.
• De-identification method. Ask how the data will be cleaned, which fields will be stripped, and whether you will review a sample before the lab receives the full set.
• License scope. Identify the field of use, geographic limits, and whether the lab seeks exclusive or shared rights.
• Term and renewal. Note the length of the license and any options to refresh the data later.
• Price drivers. Understand whether the quoted amount reflects volume, years of history, industry rarity, or inclusion of workflow capture.

Running this list against each proposal will surface any hidden differences and give you a solid basis for negotiation.

Data quality and workflow capture

AI labs value data that shows a complete request-to-outcome chain. Support tickets, CRM activity, and QA records are especially prized because they reveal the reasoning behind decisions. If your organization also records how work is performed, task runs, AI-assisted steps, or documented SOPs, those can be packaged as workflow data and priced per department. See our page on workflow data for more details.

A quick internal test helps gauge quality: pull a random sample of about 100 records and check that each entry includes a clear start, the actions taken, and the final resolution. If many records stop midway, the set will need extra cleaning before it is useful for training. Labs that receive well-structured data can train models faster and often offer higher payments.

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Compliance and de-identification

Before any lab sees the data, it must pass a test that confirms no personal information remains. The test depends on where the people in the records live, and the result is recorded in a written memo that your counsel should review.

If you want added assurance, we also provide a separate de-identification service. We map your systems, export raw files to an isolated, logged workspace, replace names with stable placeholders, and destroy the mapping key. A reviewer then attempts to re-identify individuals to measure residual risk. The cleaned data and a written record are returned to you. The service is quoted per project and is usually covered by the buying lab, but who performs the cleaning and who pays are negotiated case by case.

How the broker process works

We start by asking you a few basic questions about the data set, size, years of history, and record types you can share. You do not send any data at this stage. We create a one-page summary of your answers and share it with multiple interested AI labs. Each lab returns a quote and the conditions that fit your needs. Once you pick a preferred proposal, the button below lets us begin formal negotiations and bring the seller's summary to the lab.

Nothing moves until the seller signs off on the final quote, and the de-identified export only begins after the agreement is in place. The AI lab that purchases the data pays the broker fee after the deal closes; the seller does not incur a finder's charge.

Next steps to start licensing

1. Gather the basics about your data set, size, years of history, and record types you can share.
2. Apply the checklist above to each offer you receive.
3. When you have a preferred proposal, click the button below so we can start negotiations and bring the seller's one-page summary to the lab.

For a deeper look at how a buyer request runs through our system, see the page on how buyer requests work.

Related reading: Understanding the acceptance window in a data license