Data Annotation

Data annotation is the process of labeling unstructured data and information to train machine learning models. Today we find ourselves surrounded by high volumes of raw data. This raw data comes in unique formats like images, video, text, and audio.

Appropriately labeled, quality data is used to help supervised machine learning models identify objects, understand sentiment, and perform functions like speech recognition or even driving.

Image Annotation

Services such as bounding boxes, polygon annotations, key point annotation, LiDAR, semantic segmentation, and image classification.

Video Annotation

Labeling video footage with techniques like bounding box annotation, polygon annotations, key point annotation, and semantic segmentation

Text Annotation

Services including sentiment analysis, intent analysis, named-entity recognition (NER), and entity classification.

Audio Transcription

Transcribing audio material into text formats for machine comprehension..

Our 5-Step Process