Getty Images Summary of Training Content
Last updated: July, 2026
Public Summary of Training Content for General-Purpose AI models required by Article 53 (1)(d) of Regulation (EU) 2024/1689 (AI Act)
Provider name and contact details:
Getty Images International, Unlimited Company
10 Earlsfort Terrace, Dublin 2, Dublin, D02 T380, Ireland
Authorised representative name and contact details:
Getty Images France, SAS
RCS Paris 433 960 895
162 boulevard Haussmann, 75008 Paris
legalnotice@gettyimages.com
Versioned model name(s):
Generative AI by Getty Images (See model card here)
Model dependencies:
Bria Fibo Lite (see Bria Public Summary of Training Content for this model here)
Date of placement of the model on the Union market:
November, 2025
Modality, Training data size, Types of content:
Text, up to 120 billion tokens, image data enrichment
Image, 479 million images, fully licensed images provided by Getty Images and Bria data partners
Latest date of data: acquisition/collection for model training:
June 2025
Description of the linguistic characteristics of the overall training data:
Text training data enriched to support prompts in the following languages: English, French, German, Italian and Portuguese.
Other relevant characteristics of the overall training data:
Images training data is sourced by Bria entirely through commercial licensing agreements with Getty Images and other data partners globally, ensuring diverse representation across cultures, ethnicities, ages, genders, and geographical locations. The dataset maintains balanced coverage across domain categories while incorporating content from multiple international markets. All images training data consists of human-created content with explicit commercial use releases, deliberately excluding public figures, harmful materials, or copyrighted fictional characters.
2. List of data sources
2.1. Publicly available datasets
Have you used publicly available datasets to train the model?
No
2.2. Private non-publicly available datasets obtained from third parties
2.2.1 Datasets commercially licensed by rightsholders or their representatives
Have you concluded transactional commercial licensing agreement(s) with rightsholder(s) or with their representatives?
Yes, directly and via Bria
If yes, specify the modality(ies) of the content covered by the datasets concerned:
Images
2.2.2 Private datasets obtained from other third parties
Have you obtained private datasets from third parties that are not licensed as described in Section 2.2.1, such as data obtained from providers of private databases, or data intermediaries?
No
General description of non-publicly known private datasets obtained from third parties
All content is sourced from its rightsholders or their authorized representatives who have obtained all necessary model releases, property releases, and intellectual property clearances.
2.3. Data crawled and scraped from online sources
Were crawlers used by the provider or on behalf of?
No
2.4. User data
Was data from user interactions with the AI model (e.g. user input and prompts) used to train the model?
No
2.5 Synthetic data
Was synthetic AI-generated data created by the provider or on their behalf to train the model?
No
Information about other AI models, including provider’s own AI model(s) not available on the market, used to generate synthetic data to train the model to which this Summary applies:
N/A
2.6. Other sources of data
Have data sources other than those described in Sections 2.1 to 2.5 been used to train the model
No
3. Data processing aspects
Respect for the reservation of rights from the text and data mining exception or limitation
Are you a Signatory to the Code of Practice for general-purpose AI models that includes commitments to respect reservations of rights from the TDM exception or limitation?
No, but no data scraping is performed therefore TDM reservations n/a.
Describe the measures implemented before model training to respect reservations of rights from the text and data mining (TDM) exception or limitation expressed pursuant to Article 4(3) of Directive (EU) 2019/790 before and during data collection, including the opt-out protocols and solutions honoured by the provider or, as applicable, by third parties from which datasets have been obtained:
No data scraping is performed
3.2. Removal of illegal content
General description of measures taken:
Bria’s training data sourcing methodology inherently limits the inclusion of illegal content through the exclusive use of commercially licensed datasets obtained from verified professional data partners and established image bank providers. Each licensing agreement requires the licensor to warrant that the licensed content is original and human-created, does not infringe third-party copyright, trademark or other intellectual property rights, does not feature public figures, harmful material or copyrighted fictional characters, and is subject to all necessary model and property releases where identifiable persons or property are depicted.
Bria operates an automated cataloguing pipeline that records each asset with a clear link to its origin, applies content moderation filtering to exclude harmful material, and subjects data partners to periodic compliance audits and remediation procedures. Training datasets are fully anonymized through removal of naming and identifying metadata.