continuously
better
computer
vision
Dataset collection
Our humans collect and curate custom datasets which you can use to train your computer vision models
Dataset annotation
We label your datasets by coupling manual annotations with advanced auto-annotation and smart labeling tools
Model validation
Our humans can be plugged into the pipeline in order to verify the model’s output and handle edge cases in real time
Our advantages
EU-based and GDPR-compliant
We are headquartered in the European Union and we are fully compliant with GDPR regulations. We reduce the transfer of sensitive data at a maximum. Datasets are collected and annotated with special attention to biometric and personal data.
Transparent and flexible pricing
We use a standard hourly rate and we calculate a per-file or per-annotation price based on the amount of time they take to complete on average. We have no additional or hidden fees for quality control, project management or tool usage.
Dedicated teams and manager
We assist you in scoping your project and choosing the appropriate tool, and we complete the tasks in several iterations based on your feedback. One team works on all batches from the same client so as to develop expertise and consistency.
Trusted by
Expert labeling teams
Medical
- Radiology
- Ultrasound
- Robotic surgery
- Cardiology
- Gastroenterology
Geospatial
- Drones
- Satellite imagery
- Infrared imagery
- SAR
- Natural disasters
Automotive
- Self-driving cars
- Delivery robots
- Insurance
- Damage analysis
- Traffic monitoring
Industrial
- Manufacturing
- Recycling
- Logistics
- Construction
- PPE detection
Agriculture
- Precise farming
- Weed detection
- Plant counting
- Disease detection
- Soil analysis
Retail
- E-commerce
- Fashion
- Smart carts
- Shelf monitoring
- Shopper tracking
Social impact
We are building the next generation of professional humans in the loop from conflict-affected regions and communities
We promote AI which is diverse and bias-free and we support projects which apply AI for social good
Datasets
Plant segmentation dataset
The dataset contains 144 images of plant seedlings shot at different time intervals within the span of 2 months
Daily object detection around the world
27k images with bounding box and tag annotations released in partnership with Gapminder's Dollar Street project
Medical mask and accessory detection
6k images for detecting medical masks and other accessories, published as a contribution to the fight against COVID-19
Semantic segmentation of aerial imagery
72 images for drone and satellite vision prepared in partnership with the MBR Space Centre in Dubai, UAE
As seen on
