Case Study: NT Concepts achieves rapid training and deployment of an expert AI system with Labelbox

NTConcepts Rapid training and deployment of an expert AI system

NT Concepts, a technology-driven solution innovator working on sensitive, mission-critical national security programs, needed large volumes of accurate, consistent labeled imagery to train expert ML systems. The team faced challenges around building scalable labeling infrastructure, ongoing QA/QC of label quality, integration with cloud storage and ML pipelines, and supporting a custom, evolving ontology — so they partnered with Labelbox and its data-labeling platform to address these needs.

Using Labelbox’s interface connected to Google Cloud Platform, NT Concepts labeled tens of thousands of images (5–15 target objects per image), iteratively added classes via the editor, and used built-in metrics to monitor label accuracy and labeler productivity. Labelbox enabled rapid QA/QC (promoting top labelers to admin roles), and NT Concepts began interim model training after just one day of labeling, allowing fast iteration on labels and model parameters — accelerating deployment while reducing the need for heavy in-house investment.

NT Concepts

Zach Mostowsky

Machine Learning Engineer