Annotation Capabilities

Machine Learning models verify human judgments before they are finalized. This ensures you are only paying for quality judgements, eliminating the need for peer reviews and the risk you’re paying for judgements that don’t fit your requirements.

We support a broad range of computer vision tooling including object tracking, pixel-level semantic segmentation, and image transcription. All these image annotation services and video annotation tools support bringing your own model hypothesis for faster labeling and better model validation.  

We offer large scale text annotation and NLP labeling including named entity recognition and parts of speech labeling. All these tools support bringing your own model hypothesis for faster annotation and better model validation. We also offer computer-aided translation for machine learning projects.  

We offer a scalable audio data pipeline including collection, segmentation, event labeling, and transcription. All these data science tools support bringing your own model hypothesis for faster annotation and better model validation.

We support an extensive data collection pipeline for audio, websites, text, and images. Supported use cases include training data creation for ASR and text-based conversational agents. Any data we can see can be enriched with metadata or additional information. We use ML models to validate the quality of human submitted input to quickly complete broad-scale data collection projects.

Whether you are doing sentiment analysis, content moderation, or search relevance tuning, we offer extremely large-scale, data classification pipelines for any data classification needs. Proprietary quality control technologies allow for 95%+ accuracy and precision, with minimal effort.

Our point cloud annotation tool allows for cuboid annotation for autonomous vehicles, as well as manufacturing and agriculture. Machine aided annotation allows for large scale, time-consuming annotation to be completed quickly and accurately.