Buy AI training data from vetted sellers
The data that improves models now is private: real workflow records, expert judgment, code with its history. We find companies that hold it, vet them against a written standard and bring you evidence you can put in front of your own counsel.
How it works
You send a written requirement: data type, domain, volume, use and license terms. We search sellers, run them through eight vetting checks and send you a shortlist with a vetting file for each. You review redacted samples under NDA and contract directly with the seller you choose.
Why AI teams work with us
- 1
Every seller of training data we shortlist has passed eight vetting checks, from authority to sign through to a re-identification test.
- 2
Each shortlist comes with a vetting file per seller: rights evidence, provenance record, de-identification method, data manifest and proposed license terms.
- 3
Samples are drawn at random across the archive and labeled with the sampling method, so you can judge the whole package rather than its best rows.
- 4
You contract directly with the seller, and we help agree acceptance tests, staged payments and remedies before any data is delivered.
Where are you in sourcing?
1Exploring
What data would actually help our model?
2Weighing it up
How do we buy it without inheriting risk?
3Ready to act
Who can source it for us?
What is in a vetting file
Most diligence time is spent chasing evidence the seller never assembled. We assemble it before you see the seller.
| Rights evidence | Who signed, on what authority, and the contracts and privacy notices that permit the license |
| Provenance record | Where each record came from, which systems, which dates and what was excluded |
| De-identification method | What was removed or transformed, by whom, and the result of a re-identification test |
| Data manifest | Record counts, date ranges, languages and formats, checked against the delivery |
| Representative sample | Drawn at random across the archive under a mutual NDA, labeled with how it was drawn |
| Proposed license terms | Permitted uses, exclusivity, term, deletion and the seller's warranties |
Training data by type
What each kind of data is used for, how it is priced and the checks that matter most.
- Workplace communications dataPriced per company archive, as a flat license fee
- Customer support ticket dataPriced per ticket archive, as a flat license fee
- Source code datasetsPriced per repository or codebase, as a flat license fee
- Agent trajectory dataPriced per task or trajectory, or per environment with its taskset
- Evaluation datasetsPriced per task or per set, with exclusive access priced higher
- RLHF and preference dataPriced per comparison or per rated prompt
- Expert domain dataPriced per company archive, as a flat license fee
- Speech and audio dataPriced per hour of audio, or per archive for company recordings
- Video training dataPriced per minute of footage
- Image datasetsPriced per image, or per collection for large archives
- Multilingual text dataPriced per million words or tokens, or per archive
- Document and form dataPriced per document or page for labeled sets, per archive for company records
- Call recording dataPriced per hour of audio, or per archive for a contact center
- CRM and sales dataPriced per company archive, as a flat license fee
How we vet sellers
- 1Authority to sign. The person signing can bind the company, or the trustee, liquidator or board can act for a closed company.
- 2Ownership and chain of title. The company created or acquired the records and holds the rights to license them, including IP assignments from staff and contractors.
- 3Contract restrictions. Client contracts, NDAs, vendor terms and data processing agreements do not prohibit the proposed use.
- 4Privacy notice and lawful basis. The privacy notice in force when the data was collected, and the applicable law, allow the disclosure, or the personal data is excluded.
- 5Third-party content. Licensed content, open-source code and material owned by others is identified and either cleared or removed.
- 6De-identification method. Direct and indirect identifiers are removed by a documented method, and a re-identification test is run on a sample.
- 7Representative sample. The sample is drawn at random across the archive, not hand-picked, so a buyer can judge the whole package.
- 8Manifest accuracy. Record counts, date ranges, systems and languages in the data manifest match what is actually delivered.
What we ask of buyers
Sellers share samples because we verify buyers first. You only go through it once.
- Company identity. Registered entity, beneficial owner where relevant, and a named signatory.
- Intended use. Training, evaluation or fine-tuning, which models, and whether outputs will be commercialized.
- Security and retention. Where data will be stored, who can access it, and when raw copies are deleted.
- Onward transfer limits. Whether data may pass to affiliates, subprocessors or model partners, and on what terms.
- Ability to pay. For larger deals, evidence the buyer can meet the price and payment schedule.
Buyers pay nothing to submit a requirement or review a shortlist. Any fee is agreed in writing before an introduction.
Questions about buying data
How do I buy AI training data?
Buying AI training data starts with a written requirement: the use, data type, volume, languages and license terms you need. Then shortlist sellers, review random samples under NDA, run due diligence and sign a license with acceptance tests. You can submit a data requirement at no charge, and we will find, vet and shortlist sellers for you.
What types of training data can I source through Sell My Data To AI?
Through Sell My Data To AI you can source rights-cleared data held by companies and archives, including workplace communications, support tickets, source code, agent trajectories, evaluation sets, preference data, expert domain records, speech, video, images, multilingual text, documents, call recordings and CRM data. See training data by type for what each involves.
What is the difference between licensed and scraped training data?
Licensed training data comes with a contract from someone who holds the rights, while scraped data is collected from the web without one. Scraping can serve for prototyping, but production use needs provenance. In December 2023 the Stanford Internet Observatory reported more than 3,200 images of suspected child sexual abuse in the scraped LAION-5B dataset.
How much does AI training data cost?
AI training data costs vary by type and license. Getphyllo's reported market ranges run from $5,000 to $15,000 for research licenses to $25,000 to $500,000 or more for commercial licenses, with exclusive deals at $1 million and above. Video is quoted per minute, and Bloomberg reported Adobe paying about $2.62 on average. See AI training data pricing models.
Can I see a sample before buying data?
You can see a sample before buying data. Buyers see redacted samples under a mutual NDA, drawn at random across the archive rather than hand-picked, so you can judge the whole package. Full data moves only after the license is signed. Our guide on how to evaluate a dataset sample covers what to test.
Do I contract with Sell My Data To AI or with the seller?
You contract directly with the seller, not with Sell My Data To AI. We are a broker: we find and vet sellers, arrange samples and help agree terms, but the license is signed between you and the data owner. We do not take custody of the raw data, and we do not buy data for our own use.
Can I get exclusive rights to a dataset?
Exclusive rights to a dataset can be negotiated, at a higher price. ddiy.co's 2026 pricing guide puts exclusive deals at about 2.5 to 5 times non-exclusive ones. Exclusivity matters most for evaluation sets, which lose value once shared. Agree the scope, duration and field of use of any exclusivity in the license itself.
What license terms should a buyer insist on?
A buyer should insist on license terms that name AI training explicitly, define what may be done with derived assets such as annotations, embeddings, fine-tuned models, weights and outputs, and allocate risk through representations, indemnities, liability caps and holdbacks. Nixon Peabody's October 2026 alert sets out these points. See our licensing agreement checklist.
What should a buyer's data requirement include?
A buyer's data requirement should state the intended use, data type, domain, languages, volume, date range, delivery format, license type and budget range. Add any exclusions, such as personal data or particular jurisdictions. The more specific the requirement, the easier it is to match sellers. Submit a data requirement to start.
Is synthetic data a substitute for licensed real data?
Synthetic data can supplement licensed real data but has known gaps. MIT Technology Review reported in October 2026 that real archives avoid errors common in synthetic data, such as references to dates that do not exist, although no company has published tests comparing the two. Synthetic data generated from a licensed seed set still depends on the rights to that seed.
For AI teams
Ready to source?
Book a consultation to brief us. We shortlist vetted sellers, each with a vetting file covering rights evidence, provenance and a representative sample.