How to source industry-specific training data for AI models

You source industry-specific training data by working with a data broker who links you to companies that own the operational data you need. We collect basic information from the seller, ask a few AI labs for offers, and return the best quote for you to review.

What data is valuable

AI labs value data that captures the full chain from a request to its outcome. The most useful records include

• Support tickets together with the resolution steps taken.
• Chat threads where a decision was reached.
• CRM activity and sales-pipeline history.
• Standard operating procedures, internal documentation, and knowledge-base articles.
• Quality-assurance records and project-history logs.
• Accounting exports that show real-world financial flows.

An email archive on its own often lacks decision context, so it commands a lower price. The longer the history on the same tools, the higher the price, especially when the industry is rare or the data set is exceptionally clean.

How we match you with sellers

First you tell us what you need, describing the industry, data type, time span, and any workflow details that matter for your model. We then send a short questionnaire to potential sellers; they answer a few basic questions and no data moves at this stage. From those answers we create a one-page summary for each seller and share it with interested AI labs, never the raw data. The labs return quotes, which we compare based on price, license length, exclusivity, and any special conditions you have. We bring the best quote to you, and you decide whether to negotiate further, accept, or walk away. No contract is signed and no data moves until you give the green light, protecting your interests and keeping the process transparent.

Pricing and license terms

Deal sizes fall between $100,000 and $2 million USD; many buyers cite $200,000 to $300,000 USD as typical. The final amount depends on how much data the seller generates, the type of data (rich-context tickets are valued higher than simple logs), years of continuous history on the same tools, whether the industry is common or niche, and the cleanliness of the rights (clear ownership and ability to de-identify). Use rights are usually perpetual because a trained model cannot be reverse-engineered to reproduce the original data. Exclusivity is never perpetual; most buyers ask for a 24-month exclusive period, and a shorter term can lower the price. The seller retains ownership and continues to use the data internally.

Legal and privacy safeguards

Every dataset passes a legal check. The seller must own the data, its customer contracts must permit de-identified use, and all personally identifiable information (PII) must be removable. When a deal closes, the data is exported securely and de-identified. De-identification strips PII and any confidential markings, replacing names with stable pseudonyms such as "employee 632." Automated tools handle the bulk of the work; trained human reviewers verify the results. How raw files are handled and when they are deleted is negotiated case by case and written into the contract. The seller reviews a sample of the de-identified data before anything is accepted.

Getting started

The next step is simple: tell us the industry, data types, and time frames you are looking for. Click the button below to submit a brief request. Once we have your description, we start the matching process and bring you the most relevant offers.

[Tell us what data you need, the button below]