Data type guide

Prepare images for AI licensing

A clear chain of title for every image.

Sources and guidance · Reviewed October 2026

What makes this collection useful

Original images with consistent descriptions can support visual understanding. A collection should distinguish photographs, illustrations, scans, synthetic images and third-party stock.

Prepare before approaching buyers

Record who created each asset and what rights were acquired. Check people, locations, brands and embedded text separately. Deduplicate near-identical images before quoting volume.

Possible evaluation contexts

Visual classification; domain recognition; multimodal research. These are possible uses, not statements of current buyer demand.

Where preparation breaks down

Stock-licence restrictions, missing releases, watermarks and repeated near-duplicates.

What to put in the datasheet

Unique image count; resolution; subject coverage; caption quality; rights exceptions. State how each measure was calculated and which records were excluded. Keep the sample aligned with the collection described.

A practical next step

Create a one-page inventory, separate rights-cleared material from unresolved records and use the readiness checklist. Only then prepare a sample for a verified counterparty under appropriate evaluation terms.

Common questions

Does owning the files mean I can license them?

No. Ownership of the storage or account does not settle copyright, privacy, confidentiality or third-party restrictions. Review the rights in the content and the intended use separately.

Can I get a price without sending the full collection?

A high-level datasheet can support an initial discussion. A buyer may later request a reviewed sample and diligence; avoid sending raw archives at the first contact.

Use this as a preparation framework. It is not legal advice, a valuation or a promise that a buyer will accept your data.