AI data sourcing
How AI developers source data.
AI data sourcing is how developers obtain the data they train and test models on. The main channels are public web data, open datasets, commissioned annotation and data creation, synthetic generation, and licensing proprietary data from organisations that hold it. Licensed proprietary data is used when a model needs specialist, real-world content that other channels cannot supply.
Sourcing channels
| Channel | Strength | Limitation |
|---|---|---|
| Public web | Scale | Copyright, quality, contamination |
| Open datasets | Free, documented | Widely used, less differentiating |
| Commissioned annotation | Tailored | Costly, artificial |
| Synthetic data | Scalable, private | Lacks real variation |
| Licensed proprietary data | Specialist, real | Requires rights and preparation |
What buyers check
- Provenance and rights
- Privacy handling
- Relevance to the target task
- Format and documentation
Related
- For AI labs (/for-ai-labs)
- Data marketplace (/data-marketplace)
- Who buys business data for AI? (/insights/who-buys-business-data-for-ai)
Related resources
- SolutionProprietary data: information only your company has
- QuestionPublic data vs proprietary data: what's the difference for AI?
- SolutionTurn the data your company already creates into a licensing asset
- IndustryConstruction data
- IndustryLogistics data
- QuestionShould companies sell or license their data?
- InsightHow much is my company data worth to AI companies?
- InsightWhat kinds of business data do AI labs buy?
- InsightHow to monetize your business data: a practical guide
- DataSales and CRM data
- DataStandard operating procedures
- GlossaryDataset
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Tell us what data your company holds. No data is shared during the initial assessment.