Multimodal AI Data Use Cases Across Industries

Explore how AI teams use Unitlab to curate, annotate, review, and version multimodal training data. Connect each industry's data requirements to a practical workflow and a training-ready release.

Bounding boxes label clothing and shoes on three people.
Bounding boxes identify milk, coffee, and fruit puree products on a supermarket shelf.
Bounding boxes identify apples growing on tree branches.
Bounding boxes label cars, pedestrians, bicycles, road signs, and traffic lights in a city street.

Solutions

Explore data workflows for your industry. Curate relevant examples, annotate with shared labels, review the results, and prepare training-ready releases.
Warehouse robotic arm and automated guided vehicle handling and moving boxes on pallets in an industrial storage facility.

Robotics

Prepare robot camera images and demonstration video with object, pose, and interaction labels. Review the annotations and release consistent training data.
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Blurred crowd with red facial recognition boxes identifying three individuals with their IDs and headshots.

Video Surveillance

Annotate objects, tracks, and events in camera footage. Review temporal consistency and prepare labeled video datasets for your computer-vision models.
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Chest X-ray showing the lungs with two green highlighted areas on the upper sections of both lungs.

Health

Prepare medical images and pathology data with expert-defined labels and review workflows. Inspect annotated evidence and release datasets for medical AI research.
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Aerial view of six suburban houses with brown roofs arranged in two rows, casting shadows on green lawns and driveways.

Geospatial & Aerial

Annotate satellite, aerial, and drone imagery for mapping, remote sensing, inspection, and geospatial AI.
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Warehouse shelving filled with multiple stacked cardboard boxes labeled 'Box' and one area labeled 'Free'.

Logistics

Label packages, warehouse scenes, and shipment documents. Review object boundaries and extracted fields to prepare data for logistics AI models.
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Traffic scene on a multi-lane road with several cars, a person riding a bicycle, and a bus in the right lane.

Transportation

Annotate vehicles, road features, and traffic events in images and video. Review difficult scenes and version training datasets for transportation AI.
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Grocery store shelf displaying various almond milk and coconut milk beverage cartons and bottles with price tags.

E-Commerce

Label product images, catalog attributes, and relevant text. Review consistent classes and properties for visual search, classification, and catalog AI datasets.
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Green apples on a tree branch with AI detection boxes labeled 'Apple' around each fruit.

Agriculture

Annotate crops, visible plant conditions, and field regions in ground and aerial imagery. Prepare reviewed examples for agricultural computer-vision models.
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A cash receipt from a shop showing placeholder text for name, address, phone, item descriptions with prices, total amount, cash paid, change, and a bank card approval code.

Fintech

Annotate document fields, entities, and text categories with shared instructions. Review structured outputs and prepare versioned datasets for financial AI workflows.
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Handwritten notes explaining writing structure with headings, introduction, and main content on lined paper.

Education

Label educational text, documents, and recorded content with consistent categories and entities. Review the results and prepare datasets for learning applications.
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Portrait of a woman with facial recognition geometric lines and points overlaid on her face with a blue background.

Facial Recognition

Annotate facial regions and landmarks in your image datasets. Review label consistency and prepare evaluated examples for your computer-vision research.
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Living room with two armchairs and a coffee table highlighted with orange and blue outlines in front of a fireplace and wall clock.

Augmented Reality

Label objects, surfaces, and keypoints in real-world scenes. Review annotated image and video data for the perception models behind AR and VR experiences.
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