Our Services

Our data services across computer vision and natural language applications, support dense annotation requirements for video, image, audio, and text with complex and dynamic classifications and relationships.

Image Annotation Services

- Image annotation for the training and implementation of computer vision models.

- Object detection, anomaly detection, predictive maintenance, yield estimations, and many other use cases across multiple industries.

- Bounding boxes, polygons, semantic segmentation, polylines, cloud points.

Text Annotation for Machine Learning

- Text classification and annotation for the implementation of natural language understanding and other text related machine learning models.

- Translation, entity extraction, text classification, summarization and annotation across multiple industries and domains.

Video Annotation

- Video annotation for the training and implementation of computer vision models.

- Smart object tracking and anomaly detection in areas of security, behavior tracking, self-driving cars, and many other use cases across multiple industries.

- Process multiple frames per second with annotations of your choice.

Audio Transcription & Translation

- Offer both machine and human language specialist for text and audio translation.

- Speech to text transcriptions for the implementation of Natural Language Processing models, covert your audio/video to subtitles or text

- Transcriptions can then become the source data for our text services to allow for call summarisation, sentiment analysis and customer intent, for example

Key Facts

- Professional customer consulting including the design the entire project and shaping of the labelling specifications
- Fully managed end-to end project
- Ground Truth Annotation of vehicles, pedestrians, bi-wheelers, traffic lights and traffic signs

Key Achievements

- Achieved annotation quality target of 98%
- Often over-delivered on throughput targets
- Successfully applied various of automation components to reduce significantly manual effort
- Developed and applied a lot of validation rules serving as automated quality check, to ensure the best possible annotation quality