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BeeKeeperAI Expands Privacy-Enhancing Innovation with New Patent, New Product, and New Advantages to Accelerate Responsible AI in Healthcare

SAN FRANCISCO–(BUSINESS WIRE)–BeeKeeperAI, Inc., a pioneer in privacy-enhancing, multi-party collaboration software, today announced the next step in its innovation strategy for EscrowAI™ with automated, privacy-enhancing workflows to advance the responsible development and deployment of AI for healthcare.

The company is expanding its novel privacy-enhancing capabilities to address confidential federation and confidential training in ways that continue to accelerate the approval processes for healthcare algorithm development by protecting data sovereignty, patient privacy, and intellectual property (IP) while at rest, in transit, and also during the compute cycle.

BeeKeeperAI is unveiling a breakthrough new IP-protecting patent that catapults the company’s approach to confidential federated training ahead of the conventional approach to federated learning, which is not capable of protecting the data and IP during model training and aggregation.

The company is also unveiling enhancements to its EscrowAI platform, which utilizes Microsoft Azure confidential computing to resolve the challenges of data sovereignty, privacy, and security. BeeKeeperAI is announcing the availability of the industry’s first software-as-a-service (SaaS)-based workflow application leveraging Microsoft’s groundbreaking Confidential Containers on Azure Container Instances to provide algorithm developers with a choice of the Trusted Execution Environment (TEE) that meets their model’s needs.

“The work that BeeKeeperAI has done to simplify, accelerate, and fully secure AI collaboration environments is critical for the advancement of AI in healthcare,” said Dr. Michael Blum, MD, Co-founder and Chief Executive Officer at BeeKeeperAI. “As we break new ground with privacy-enhancing capabilities, our IP and resulting software have advanced beyond anything else available in the marketplace today, positioning BeeKeeperAI with a first mover advantage that defines the future of confidential algorithm development and deployment. No other approach – not even federated learning – can come close to the high level of security, privacy, flexibility, and efficiency that our approach delivers, without compromising usability.”

Data stewards, such as chief information officers, chief data officers, and chief innovation officers, among others, need to ensure proper data security and governance are maintained while they work to fulfill their mission of scientific innovation leveraging their institution’s data. In parallel, algorithm developers need access to diverse, high-quality data to train and validate algorithms for use in care settings.

BeeKeeperAI solves these fundamental problems for both healthcare data stewards and algorithm developers. EscrowAI’s collaboration solution protects the intellectual property and data privacy using a solution that integrates and automates the use of TEEs within the data steward’s secure data environment, delivering encrypted protection of the data and IP during the computing cycle and full isolation of the computing resource. This solution delivers the most secure, state-of-the-art, privacy-enhancing solution available.

Because of its end-to-end encryption and additional controls ensuring the training process is tamper-proof, BeeKeeperAI’s patented approach to federated learning is more secure than conventional methods that have the potential to expose information during the training process. Unsecured federated training leaves open the potential for partial or full data set and model reconstruction that could cause compliance problems for healthcare institutions, expose the IP of new health innovations, cause vulnerabilities to cyberattacks and security breaches, and undermine the IP of developers.

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