Multimodal data
Data whose meaning lives in more than one medium at once: images and video with structured annotation, sensor and viewpoint recordings, and the question-answer pairs built on top of them. These are the categories behind vision-language models and the systems that read the physical world.
What counts as multimodal data
Multimodal data is where one sample carries more than one kind of signal: an image with its annotation, a video with temporal labels, a sensor stream paired with the language that describes it. The category is defined by the pairing rather than by the medium. A folder of photographs is image data; the same photographs with structured captions, bounding boxes or question-answer pairs are multimodal.
What makes it hard is alignment. The annotation has to agree with the media at the level the model reads: a box has to sit on the object it names, a temporal label has to match the span it describes, and a question-answer pair has to be answerable from the frame it references. Most defects in multimodal data are alignment defects, and they are created at annotation time rather than in delivery review.
The categories in this collection
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Computer Vision Data
Annotated image and video data, with annotation types including classification, bounding boxes, segmentation masks, and keypoints.
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Video Data
Annotated video footage, with the annotation needed for tasks such as action recognition, object tracking, and temporal segmentation.
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Satellite Imagery Data
Remote-sensing satellite or aerial imagery, with multispectral bands and geographic annotation, used for land-cover classification, change detection, and agricultural monitoring.
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First-Person View Data
Video and sensor data captured from the operator's viewpoint with wearable devices, used for embodied AI and action understanding.
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Autonomous Driving Data
Road-scene data captured by vehicle sensors (cameras, lidar, and annotation boxes), used to train perception models.
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Embodied AI Data
Multimodal data generated as robots and embodied agents operate in real environments: vision, action trajectories, and language instructions.
Submit a sourcing request
Tell us the language, the hours, and what the data needs to look like. You will get a real number and a real timeline, not a range. If we cannot source it well, we will tell you that instead.
- Pilot batch before the full run, so problems surface early.
- Consent documentation delivered with the data.
- No medical or clinical data. No recorded telephone calls.
- You send the spec Language, hours, recording conditions, and the deadline.
- We reply within two business days A real number and a real timeline, not a range.
- You approve a pilot batch A small run first, so problems surface before the full order.
- Full run, then delivery with documents Audio, transcripts, and the consent record for every speaker.