Latest news with #BeeKeeperAI
Business Wire
27-05-2025
- Health
- Business Wire
BeeKeeperAI Enables Icahn School of Medicine at Mount Sinai and Morehouse School of Medicine to Test the Performance of Healthcare AI Models in Their Environments
AUSTIN, Texas--(BUSINESS WIRE)--BeeKeeperAI®, Inc., a pioneer in privacy-enhancing, multi-party collaboration software for AI development and deployment, today announced that Morehouse School of Medicine (MSM) and the Icahn School of Medicine at Mount Sinai will utilize BeeKeeperAI's EscrowAI® platform to rapidly test AI models on their real-world, multi-modal data in chronic heart failure (CHF). This milestone represents the first operational deployment certified under the Coalition for Health AI (CHAI)'s assurance service provider certification process, setting a precedent for how AI models can be responsibly tested and brought to market faster across institutions and populations. 'As we advance our mission to enable responsible, evidence-based AI, this is just the first of many collaborations where CHAI-certified service providers and health institutions will work together to ensure AI serves all patients,' said Dr. Brian Anderson, CEO of CHAI. 'We're proud to see Morehouse School of Medicine, Icahn School of Medicine, and BeeKeeperAI leading the way in developing trusted AI solutions.' MSM, Icahn School of Medicine, and BeeKeeperAI are all members of CHAI and have adopted its scorecard model for algorithm developers seeking to demonstrate real-world performance to the broader market. Their shared goal is to accelerate the responsible development, validation, and market adoption of AI that improves clinical decision-making, reduces hospital readmissions, and ensures needs-based outcomes—particularly for patients with lower resource availability who face disproportionate risk from chronic heart failure. 'To bring healthcare AI to market, speed matters—but so does trust,' said Dr. Michael Blum, MD, Co-founder and CEO of BeeKeeperAI. 'With EscrowAI, Icahn School of Medicine and Morehouse School of Medicine can enable AI developers to securely test their models on high-value, real-world data in days—not months—while preserving patient privacy and model IP. This is how we unlock faster, scalable, and equitable innovation in healthcare.' The curated datasets, based on shared specifications, include clinical, demographic, and social determinants of health data—offering a rare opportunity to assess algorithm performance across institutions serving predominantly resource-limited populations. 'Morehouse School of Medicine is committed to ensuring all patients have the opportunity to achieve optimal outcomes from treatment for chronic heart failure,' said Muhammed Y. Idris, PhD, Assistant Professor, Medicine and Co-Director, Center for the Validation of Digital Health Technologies and Clinical Algorithms at Morehouse School of Medicine. 'By enabling AI developers to securely compute on our data, we're creating the foundation for algorithms that can reduce readmissions and mortality for those most at risk.' 'AI has the potential to transform clinical care delivery, but only if models are proven to be accurate, safe, and effective in real-world and diverse settings,' said Tanvir Kahlon, MD, MBA, Assistant Professor, Advanced Heart Failure and Transplant, Interventional Cardiology at Icahn School of Medicine at Mount Sinai. 'Our work with BeeKeeperAI and Morehouse makes that assurance possible—without compromising privacy or integrity.' Accelerating Trustworthy & Responsible AI with Privacy-Enhancing Technology BeeKeeperAI's EscrowAI platform allows AI model testing inside a data steward's secure environment using Trusted Execution Environments (TEEs) with confidential computing—ensuring data privacy, regulatory compliance, and protection of IP throughout the process. As a recently certified CHAI Assurance Service Provider, BeeKeeperAI meets the highest standards for ethical and secure AI validation. EscrowAI replaces lengthy data access and contracting delays with push-button, compliant testing workflows —compressing timelines and accelerating time-to-value for algorithm developers. Developers can test and prove model performance on real-world, regulated data in a SOC 2-compliant environment aligned with CHAI's data integrity and scorecard framework. The resulting performance reports are immutable, transparent, and reproducible—creating a fast, scalable path to market evaluation and adoption. CHAI Assurance: A Market-Based Model for Responsible AI This collaboration reflects a broader shift in healthcare AI—from evaluations too often based on marketing presentations to more evidence-based, transparent assurance. CHAI's conflict-of-interest and ethics policies ensure independent oversight, while BeeKeeperAI's infrastructure delivers privacy-protected reproducibility, regulatory-grade audit trails, and speed-to-deployment. Together, they support faster validation and value-based procurement for AI solutions that work, including in populations that need them most. As part of this initiative, Icahn School of Medicine and Morehouse School of Medicine will be publishing data catalogs, enabling independent AI testing and validation to support the new benchmark for healthcare AI transparency and efficiency. About BeeKeeperAI BeeKeeperAI is the pioneer in privacy-enhancing technologies, integrating Trusted Execution Environments with confidential computing to accelerate AI validation and deployment in regulated sectors, including healthcare and government. BeeKeeperAI enables real-world data to be used safely and securely, without ever exposing it—empowering institutions to bring trusted AI to market faster. Learn more at Icahn School of Medicine at Mount Sinai is an investor in BeeKeeperAI.
Business Wire
15-05-2025
- Health
- Business Wire
BeeKeeperAI and cStructure Collaborate to Advance Causal AI for Scientific Advancement and Healthcare Innovation
AUSTIN, Texas--(BUSINESS WIRE)-- BeeKeeperAI ®, Inc., a pioneer in privacy-enhancing, multi-party collaboration software for AI development and deployment, and cStructure, a leading innovator in collaborative causal inference, today announced a collaboration for advancing causal AI to speed up the ability of scientists, health data stewards and AI algorithm developers to build and train AI models that can be trusted for scientific advancement and healthcare innovation. Causal AI is one of the next big frontiers for GenAI to be successful and more widely trusted in the healthcare and scientific fields − going far beyond just identifying patterns as traditional AI is known to do. The two companies are pioneering a novel, causal AI-centric approach that preserves patient data privacy, while enabling transparency, at scale, to better understand and model cause-and-effect relationships within health-related data, including data from large populations. The rigorous data analysis is captured in causal graphs that can be reliably used in high-quality, regulatory-grade life science. Ultimately, causal AI makes GenAI more trustworthy and compliant with regulatory-based best practices. To kick off this collaboration, BeeKeeperAI and cStructure are launching the ' Covid Causal Diagram DREAM Challenge,' a crowd-sourcing initiative that opens up access for scientists to analyze real-world COVID data from the National Institutes of Health (NIH) in a privacy-enhancing environment for the purpose of accelerating the determination of the causal relationships between treatment and patient outcomes. Causal AI is one of the next big frontiers for GenAI to be successful and more widely trusted in the healthcare and scientific fields − going far beyond just identifying patterns as traditional AI is known to do. Causal AI is an answer to the struggles of GenAI to consistently deliver the best possible factual information. Causal AI is designed to explain why something happened and what will happen. It is also a key to speeding up how regulatory bodies, such as the FDA, evaluate clinical studies that use AI. Critical to the advancement of causal AI are transparency, data privacy, efficiency and global access to real-world data. 'Our collaboration with cStructure is a perfect match to leverage GenAI for innovation at the speed of industry, combining BeeKeeperAI's privacy-preserving EscrowAI data platform and cStructure's causal diagram tech to accelerate the adoption of causal AI for improving human health,' said Dr. Michael Blum, MD, Co-founder and Chief Executive Officer at BeeKeeperAI. 'We're excited about our first project with cStructure to address the challenges of AI in health-centric applications. Through the DREAM Challenge, biomedical scientists will be able to compute on NIH data in our privacy-enhancing EscrowAI environment and have teams collaborate to build causal graphs. The results have the potential to change the way that the community thinks about causal relationships and transparency of AI in healthcare.' Erick R. Scott, MD, Founder of cStructure, said, 'We have made significant progress at cStructure in establishing a collaborative interface for developing causal diagrams that visually represent treatment effects, confounders, and outcomes. A necessary complement is a secure collaboration environment where AI models can compute on sensitive data while preserving privacy and protecting the intellectual property of the model. BeeKeeperAI delivers a privacy-preserving platform that automates the use of confidential computing, which provides the highest level of security for AI. We're proud to partner with BeeKeeperAI on the Covid Causal Diagram DREAM Challenge and on the opportunity to make causal AI mainstream for science and healthcare.' The DREAM Challenge Covid Causal Diagram DREAM Challenge asks participants to develop Structural Causal Models (SCMs) with the assistance of Large Language Models (LLMs). This causal diagram challenge focuses on the effect of glucocorticoids on 28-day survival rates in hospitalized COVID-19 patients. The challenge opens May 15, 2025. The cStructure platform provides a collaborative causal graph interface that participants will use to develop models specifying relationships between patient characteristics, treatments, and outcomes. An integrated large language model assistant offers domain expertise and support. Challenge participants will have access to real-world data collected in NYC during the early stages of the global pandemic to train their SCMs. At the end of the challenge, submitted models will be securely evaluated within the remote EscrowAI enclave using data collected during a fit-for-purpose cohort study to simulate federated learning. 'We at DREAM Challenges are thrilled to work with cStructure and BeeKeeperAI on the Covid Causal Diagram DREAM Challenge — a groundbreaking effort and bold step toward harnessing causal AI to answer critical questions in medicine. By combining privacy-preserving technology with global scientific collaboration, we are advancing a future where AI not only predicts but explains, driving real breakthroughs for patient care,' said Gustavo Stolovitzky, PhD, Founder, Chair Emeritus and Director of DREAM Challenges. Models will be assessed on the following criteria: comparison with high-quality randomized controlled trial (RCT) results; proper adjustment for confounding; and plausibility of causal relationships in the submitted model. About cStructure cStructure transforms how teams understand cause and effect in complex data. Our intuitive platform merges generative AI capabilities with robust causal reasoning, enabling researchers to discover meaningful relationships without specialized statistical expertise. By visualizing causal relationships in an accessible collaborative environment, we help organizations across healthcare, academia, and industry extract trustworthy insights that drive innovation. Our collaborative approach embodies our core belief: Causality. Simplified. For more information, visit About BeeKeeperAI BeeKeeperAI is the pioneer in privacy-enhancing technologies, leveraging Trusted Execution Environments with confidential computing for the development and deployment of AI in regulated data industries, including healthcare and government. BeeKeeperAI is accelerating the broader availability of AI-powered solutions that will help to redefine the future of healthcare, commerce and government. For more information, go to
