Announcing our $15M Series A led by Matrix Partners to annotate the world's medical data
We are so humbled and excited to share our recent $15M Series A funding round led by Matrix Partners!
Sep 3, 2021
Centaur Spotlight: Tom Gellatly
Today, we’re getting to know Tom Gellatly, a Centaur Labs co-founder and the VP of engineering!
Aug 4, 2021
Brigham and Women's Hospital teams up with Centaur Labs on Massachusetts Life Sciences funded project (via Mass Life Sciences)
Fourteen projects receiving funding to support R&D, innovation in addressing challenges in therapeutic delivery and unlocking potential of data science to answer pressing life sciences questions.
Jul 8, 2021
Our data-driven approach to QA
Medical assessments are rarely black and white. To handle the grey, we offer a rigorous, data-driven approach to QA.
Mar 29, 2021
An interview with CEO Erik Duhaime (via AIMed)
Founder and CEO of Centaur Labs talks to AI Med magazine about the power of collective intelligence.
Feb 18, 2021
From MVP to scaleup: how to 10X your medical data labeling pipeline
Understand why traditional labeling pipelines are so hard to scale and learn how our solution can 10X your labeling pipeline in a shorter time frame and with higher accuracy
Jan 10, 2021
When experts disagree, who do you trust for your medical AI?
Learn the how to mitigate the impact of medical error in your data labeling pipeline by intelligently aggregating multiple expert opinions together
Dec 8, 2020
Our collection of open source datasets for medical AI
Access a collection of dozens of open source image datasets for medical AI across a variety of formats including X-ray, CT, Ultrasound, Whole Slide Imagery, MRI and more
Dec 3, 2020
The power of metadata
Understand how Centaur Labs' data annotation platform offers richer results than traditional data labeling vendors
Oct 20, 2020
Building a scalable and accurate medical data labeling pipeline
Examine the unique challenges with medical data labeling, the relative lack of accuracy produced by traditional data labeling methods, and discover a more accurate and scalable alternative
Aug 1, 2020