Multimodal AI Datasets
Licensed multimodal datasets combining images, video, text, captions, metadata, and labels for commercial AI development.
Wavebreak Media provides rights-cleared image-text, video-text, captioned, and metadata-rich datasets with structured relationships between modalities.
Featured Datasets
Explore sample licensed datasets across image, video, audio, and text collections.
Multimodal Data for Cross-Modal AI Systems
Multimodal datasets connect visual media with text and structured information so models can use relationships between modalities rather than isolated assets. Wavebreak Media can organize licensed data around image-text, video-text, captions, metadata, labels, question-answer fields, or custom schemas defined by the model task.
Multimodal Pairing and Dataset Structure
Related data elements can be linked through unique identifiers, manifests, structured records, file relationships, or custom schemas so each modality can be reliably matched during model development.
- Image-text and video-text relationships
- Captioned image and video collections
- Visual media with categories, attributes, and structured metadata
- Question-answer fields where required
- Unique identifiers, manifests, and custom relationship schemas
- Dataset enrichment, annotation, rights documentation, and secure delivery
Built for Cross-Modal Understanding and Retrieval
Multimodal datasets can support workflows that depend on reliable relationships between visual, textual, and structured data.
Depending on the project, datasets can support:
- Visual-text matching and cross-modal alignment
- Cross-modal search and retrieval
- Cross-modal model evaluation
- Media-to-metadata and attribute relationships
- Custom linked-data workflows
Multimodal Dataset Options And Commercial Licensing
Image-text datasets
Images paired with captions, descriptions, labels, tags, or other structured text fields.
Video-text datasets
Video paired with captions, descriptions, scene context, labels, metadata, or other structured text.
Custom multimodal datasets
Define pairing, schema, curation, annotation, metadata, rights, and delivery requirements for a custom multimodal dataset.
Custom Dataset CreationFrequently Asked Questions (FAQ)
Multimodal AI datasets are structured datasets that combine more than one type of data, such as images with captions, videos with descriptions, visual media with metadata, or media files with labels and text fields. These datasets help AI systems learn relationships between visual content and language.
Image-text datasets pair still images with associated text, such as captions, descriptions, category labels, or keyword tags, so models can learn to connect visual content with written meaning.
Yes. Wavebreak Media provides licensed, rights-cleared multimodal datasets with documentation intended to support commercial AI training, evaluation, and product use.
Multimodal datasets sourced through Wavebreak Media are prepared with licensing documentation and commercial usage terms intended to support use in commercial AI products, not just research.
Multimodal datasets explicitly link two or more data types through structured relationships, such as images paired with captions or videos paired with descriptions. A general AI training dataset may contain only one modality or may not define relationships between modalities.
Video-text datasets pair video content with associated text, such as scene descriptions, captions, or metadata, so models can learn to connect motion, context, and events in video with written meaning.
Yes. Wavebreak Media can source or create custom multimodal datasets tailored to specific model workflows, including media format, paired text requirements, captions, metadata fields, dataset size, and delivery timeline.
Request Multimodal AI Datasets
Tell us what type of multimodal dataset you need, including media format, paired text requirements, captions, metadata fields, dataset size, release requirements, and delivery timeline. Wavebreak Media will review available and custom dataset options for your multimodal AI workflow.
