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Centaur.ai has teamed up with Consensus, an emerging AI-powered scientific search engine, to accelerate AI development with high-quality, expert annotations. Faced with the challenge of extracting precise information from scientific literature, Consensus turned to Centaur.ai’s collective labeling platform, which combines robust software with a vetted network of scientists and doctors.
In just two weeks, Centaur.ai delivered over 100,000 unique expert labels, meeting Consensus’s needs for scale and accuracy. “Because of the unique Centaur.ai data labeling solution that not only provides the software to complete labeling tasks but also provides a network of experts… it was a no-brainer to work together,” said Consensus CEO Eric Olson. Centaur.ai managed the full lifecycle, from sourcing annotators to quality assurance, allowing Consensus to focus on refining its models. That rapid success laid the foundation for an ongoing collaboration to ensure their AI continues delivering the most accurate scientific insights.
Erik Duhaime, co-founder and CEO of Centaur.ai, reaffirmed the company’s commitment to advancing AI through expert-driven data: “We’re excited to partner with teams on the cutting edge of healthcare and AI… We’re thrilled to support them both as they move to general availability.” Moving forward, both teams aim to leverage this synergy to offer users instant access to rigorously vetted research findings, underpinned by scalable, collective expert intelligence.
Meet Centaur.ai at HIMSS 2026 in Las Vegas at booth #11222. See live demos of our collective intelligence platform that produces superhuman data for healthcare AI training, evaluation, and validation. Learn how higher-quality data improves model performance, reduces risk, and accelerates clinical AI deployment with measurable confidence.
A $750,000 grant from the Massachusetts Life Sciences Center will support Brigham & Women’s Hospital researchers in their efforts to transform medical research.
Healthcare AI success depends more on data quality than data volume. This blog explores insights from The Lancet Digital Health and explains how high-quality annotations, validation, and governance improve model reliability. Learn why Centaur.ai focuses on trusted datasets and expert intelligence to build AI systems that perform safely in real-world clinical environments.