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VettedHive

Labeled data for the teams building AI

Every industry has its own edge cases. Here is what a typical project looks like in each one, drawn on real images the way we deliver them.

Trusted by data teams at

  • Innodata
  • Shaip
  • Intellisane AI
  • MindEarth

Image · Video · LiDAR

Autonomous driving

Perception teams need every vehicle, lane and sign labeled the same way across millions of frames. We follow your taxonomy to the letter, including occlusion, truncation and the edge cases your guideline hasn't thought of yet.

  • 2D boxes and 3D cuboids
  • Lane and road-edge polylines
  • Multi-object tracking
  • Traffic sign and light classes
Motorway traffic with cars, a van and a truck boxed and lane lines traced

Image · Drone / aerial

Agriculture

Aerial and ground imagery for crop health, yield estimates and farm mapping, labeled against a class guide with pictured examples of every crop stage and weed you care about.

  • Field and crop-row segmentation
  • Weed vs crop masks
  • Fruit and plant counting
  • Farm asset detection
Aerial view of farmland with the crop field segmented and the barn, solar array and vehicles labeled

Image · Text

Retail & e-commerce

Product photos and shelf images turned into clean catalogue data: categories, colours, materials and every attribute your search and recommendation models filter on.

  • Product attribute tagging
  • Shelf and planogram audits
  • Bounding boxes per SKU
  • Catalogue de-duplication
Product photo of a sneaker with a bounding box and catalogue attributes

Image · Text

Healthcare

Organ and region segmentation on de-identified scans, plus clinical text tagging. Access follows your data-handling rules, and labels go to your clinicians for review where your protocol requires it.

  • Organ and region segmentation
  • Finding-level boxes
  • Clinical entity tagging
  • De-identification checks
Chest X-ray with both lungs and the heart outlined as segmentation masks

Image · Video · Point cloud

Robotics & drones

Manipulation and navigation data: where to grip, what to avoid, and what changed since the last pass. We label from the robot's camera view, so labels match what the model will actually see.

  • Grasp-point keypoints
  • Object and gripper boxes
  • Obstacle segmentation
  • Inspection defect tagging
Robot gripper picking up an assay plate, with object and gripper boxes and two grasp points

Text · Image · Audio

Generative AI

Human judgement for language and multimodal models: preference rankings, rubric scores and written demonstrations, in English and native-speaker Bengali.

  • Preference ranking
  • Rubric-based evaluation
  • Prompt and response writing
  • Bengali data collection
Hand on a laptop keyboard with a Bengali prompt, model answer and rubric scores overlaid

Working in another industry?

Send us a sample and your label guide. We’ll tell you honestly whether we’re a fit, and label a pilot batch for free.

Request a free pilot