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We Create Superior Data By Making Annotation Competitive
The best AI models aren’t just trained and evaluated with human data; they’re built with superhuman data. The strongest datasets emerge through collective intelligence, where humans and machines work together to outperform either one alone. At Centaur, we create superior quality data by turning annotation into an arena where experts and AI compete.
Centaur AI provides expert data annotation services for AI, combining human and AI inputs to create high-quality, research-grade datasets across multiple industries and data types. Their approach emphasizes competitive annotation and a production-ready data delivery via API and standard formats.
Centaur offers multimodal data labeling and model evaluation services. Clients bring raw data or problem statements, and Centaur designs datasets,Paired with a marketplace of 100,000+ subject matter experts and/or AI models to annotate. They aggregate signals from both human and AI annotators, continuously measure performance, and deploy production-ready data via API, JSON, CSV, or DICOM. They also provide an interactive quality playground to test labeling strategies and visualize cost versus accuracy, with security and privacy practices in place.
Who it’s for: AI teams and organizations seeking scalable, high-quality annotated data for medical, life sciences, insurance, consumer, retail, robotics/manufacturing, and LLM/software applications.
Hiring/traction indicated by large-scale data labeling platform features and interactive tools; ongoing product demos and case studies suggest active commercialization.
Hello! I live in Durham, NC. I have a background in mobile and web development and engineering management. I studied CSE at the University of Michigan. I was the first employee at SF ride-sharing startup Sidecar, which was acquired by General Motors in 2016. I then managed the mapping & data labeling engineering teams at Cruise Automation for 1.5 years.
I'm a self-taught, generalist software engineer. I cofounded Centaur Labs in 2017. Previously I worked as a full-stack software engineer at Washington City Paper, where many notable people in media got their start.
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