RedBrick AI
A software platform designed for radiology AI teams to build and scale ground truth data, focusing on rapid medical data annotation.
About RedBrick AI
RedBrick AI's mission is to accelerate the adoption of artificial intelligence in radiology by building world-class software infrastructure. Currently, we are focused on helping radiology AI teams prepare high-quality datasets to train their algorithms.
Radiology data, such as CT and X-ray scans, is an incredibly important source of truth in healthcare delivery. In fact, over 90% of all healthcare data is medical imagery! However, the global radiology workforce is overburdened. In the UK, for example, only 2% of radiology departments are able to fulfill their reporting requirements, and this trend is reflected worldwide.
The acute state of radiology, coupled with the abundance of data, makes the use of AI in radiology a prime candidate. In 2022, $5.6 billion was invested in the development of AI in healthcare! However, a key hindrance to further adoption is the lack of sophisticated tools to build and deploy AI algorithms in clinical environments. This is the problem we’re focused on at RedBrick AI
We're a team based out of Bangalore India, and USA. We're backed by leading institutional investors like Y Combinator and Peak XV (formerly Sequoia Capital India).
Products
A browser-based radiology data annotation platform that supports DICOM viewing, 3D contouring, and AI-assisted segmentation.
What customers say
RedBrick AI reports that Qure.ai uses its platform for scan annotation, consensus review, real-time label validation, and a clinical performance study. The case study reports easier annotator onboarding, faster scan…
Case studyRedBrick AI reports that Olea Medical uses its platform to manage medical-image annotation and collaborate with external labelers while retaining data in its own cloud storage. The case study reports a faster annotation…
Case studyRedBrick AI reports that RapidAI adopted its platform for stroke and cardiovascular annotation projects. The case study describes annotating reconstructed image views in one window and using multi-tier review workflows…
Case study
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