Summary
This is a descriptive snapshot of Bright Info's published research, not a census of transactions or a survey of private buyer budgets. The underlying comparison records 71 entities, including Bright Info; the directory contains 70 external company profiles.
For company-level citations, see the research directory and sources and methodology.
2026 market map and categories
The 71-company comparison groups organizations into 24 AI data vendors, 16 marketplaces, 3 wind-down buyers, 8 AI labs, 19 brokers including Bright Info, and 1 big-tech infrastructure provider.
These categories describe business models. Being listed does not mean an organization is currently buying all kinds of company data or inviting unsolicited samples.
How the types differ
AI data vendors may license and package records for downstream model labs. Marketplaces provide discovery or licensing infrastructure. Wind-down firms focus on closing businesses. AI labs may contract directly or through vendors. Brokers may advise or represent sellers.
Payment models are not directly comparable without normalizing term, exclusivity, data quality, onward-transfer rights and processing costs.
What pricing evidence can support
The source-backed research includes published programs, reported deal ranges and unusual large asset-auction examples. These should not be averaged to infer a typical company's payout.
Where a buyer profile says 'Not published,' the dataset does not establish a price. This report makes no claim about realized average transaction value.
Methodology, date and limitations
The source is the public JSON buyer dataset and individual profile citations, verified as described by Bright Info on November 3, 2026. It distinguishes self-reported company statements from independent public reporting and records missing fields.
This is not an exhaustive list of all AI training-data purchasers, an endorsement of counterparties or evidence that a private deal took place. Corrections: hello@brightinfo.com.
Practical takeaways for sellers
Establish rights to license the proposed records before sending samples. Compare eligible counterparties on precisely defined data scope, permitted uses and privacy controls. Use written bids rather than broad promotional price ranges.
For next steps see selling company data, valuation and the license checklist.
Related guides and research
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