RedBrick AI, a Michigan, MI, and India-based healthtech startup, raised $4.6 million in seed funding to accelerate the development and adoption of artificial intelligence in clinical settings, through rapid data annotation on medical imagery.
The round was led by Surge, the scale-up program run by Sequoia Capital India, with participation from Y Combinator and a number of business angels.
The funds raised will be used for the growth of the engineering team in India and to expand the suite of products.
"With the rapid growth of artificial intelligence in clinical settings, researchers need excellent tools to build high-quality datasets and models at scale. Our customers are in the vanguard of this growth, pioneering everything from surgical robots to automated detection of cancers. The new funds will be integral to the growth of our engineering team in India and to expand our suite of products. We're incredibly excited to be powering the next generation of researchers in building AI for clinical settings," said Shivam Sharma, co-founder, and CEO, of RedBrick AI.
The platform's specialized annotation tools can be accessed through the browser and are designed to be used without prior training. Its API also helps machine learning engineers integrate with their cloud and clinical data stores, for example, AWS or hospital enterprise PACS servers.
Company: RedBrick AI
Round: Seed Round
Funding Month: November 2022
Lead Investors: Surge
Additional Investors: Y Combinator
Company Website: https://redbrickai.com/
Software Category: Medical Annotation Tools
About the Company: Founded in 2021 by Shivam Sharma and Derek Lukacs, the RedBrick AI is a SaaS platform that offers high-performance web annotation tools for 2D and 3D data to give experts access to specialized tooling right from their browsers. It offers specialized annotation tools that can be accessed through a web browser and integrated within customers’ existing data storage systems, such as AWS, Google Cloud Platform, and Azure. RedBrick AI additionally provides APIs that machine learning engineers can integrate with their cloud solutions and clinical data stores, including hospital enterprise PACS servers.