Data labeling is the most critical factor in building effective machine learning models. HelloGov is committed to being the leading federal data labeling provider and helping agencies realize the full benefits of AI.
Obtain greater control over annotation workflows with seamless integration into your agency's pipeline. Carnegie Studio™ makes it possible for non-technical federal users to create granular, plug-and-play, multi-step annotation projects. Remove bottlenecks and lower the costs of data annotation like never before.Get Started
Create faster models directly on video with label analytics. Leverage our workbench to draw 2D or 3D bounding boxes for a wide range of federal use cases. Annotate irregular objects with polygons with percision. Add annotations and accurately label anatomical or structural points of interest from the simple (i.e. facial recognition) to more complex (i.e. emotion detection) use cases.
Advanced image labeling with accurate classification, object detection, and segmentation tools to support federal use cases.
Carnegie Studio™ learns high precision predictions from your image annotations, automating simple labels that empower federal teams to create higher quality labels.
Label conversations, documents, paragraphs or text strings efficiently and rapidly with text classification, named entity recognition and complex ontologies. Automatically annotate, classify & disambiguate entities and documents. Draw relationships or plug your ML model in and use the feedback to train it.
Use Carnegie Studio™ as a library of simple building blocks to construct custom labels with the ability to cross-reference audio, video, text and metadata. Our deep learning labeling technology offers audio transcription, classification, and annotation with a model in the loop (pre-trained models) to help agencies label segments and bootstrap manual annotations.
Deploy to the cloud via AWS GovCloud / Microsoft Azure or as on-premise, hardware-agnostic, containerized solution.