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Blog

Building AI that actually works in healthcare isn’t about clever prompts or bigger GPUs. It’s about proof: Can your model handle the messy edge cases a clinician will see on day one? Can you explain—line by line—why it gave that answer, and who confirmed it’s correct?
That’s the gap Autoblocks and Centaur.AI are closing together.
Individually, we each make your model smarter. Together, we give you an evidence trail a regulator (and your medical director) will actually trust.
Expert-quality data labels from Centaur Labs are consistently more accurate than those gathered using traditional methods—Autoblocks ingests the results automatically.
Push a new prompt or parameter set in the morning; by lunch you’ve got edge-case scores and expert comments.
Every test, every annotation, and every fix is time-stamped and exportable. SOC 2 auditors love us; your legal team will too.
No more “pray and spray.” When the dashboards are green—you go live.
We’re opening a short beta window for teams shipping AI in regulated environments. Beta partners will:
⚡️ The waitlist takes 30 seconds. If “HIPAA” or “FDA” slides are in your next board deck, this is for you.
Speed used to be at odds with safety. Not anymore. Autoblocks ✕ Centaur.AI gives you both—so you can focus on building the future of healthcare instead of firefighting the past.
See you in the beta. Let’s raise the bar together.
Centaur.AI collaborated with Microsoft Research and the University of Alicante to create PadChest-GR, the first multimodal, bilingual, sentence-level dataset for grounded radiology reporting. This breakthrough enables AI models to justify diagnostic claims with visual references, improving transparency and reliability in medical AI.
Understand how Centaur Labs' data annotation platform offers richer results than traditional data labeling vendors
In the era of hybrid work, creativity and thoughtfulness are key to team success. Learn how we’re helping our team thrive, no matter where they work.