Opaque Systems, the pioneers of secure multi-party analytics and AI for Confidential Computing, announced the latest advancements in Confidential AI and Analytics with the unveiling of its platform. The Opaque platform, built to unlock use cases in Confidential Computing, is created by the inventors of the popular MC2 open source project which was conceived in the RISELab at UC Berkeley. The Opaque Platform uniquely enables data scientists within and across organizations to securely share data and perform collaborative analytics directly on encrypted data protected by Trusted Execution Environments (TEEs). The platform further accelerates Confidential Computing use cases by enabling data scientists to leverage their existing SQL and Python skills to run analytics and machine learning while working with confidential data, overcoming the data analytics challenges inherent in TEEs due to their strict protection of how data is accessed and used. The Opaque platform advancements come on the heels of Opaque announcing its $22M Series A funding,
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Confidential Computing – projected to be a $54B market by 2026 by the Everest Group – provides a solution using TEEs or ‘enclaves’ that encrypt data during computation, isolating it from access, exposure and threats. However, TEEs have historically been challenging for data scientists due to the restricted access to data, lack of tools that enable data sharing and collaborative analytics, and the highly specialized skills needed to work with data encrypted in TEEs. The Opaque Platform overcomes these challenges by providing the first multi-party confidential analytics and AI solution that makes it possible to run frictionless analytics on encrypted data within TEEs, enable secure data sharing, and for the first time, enable multiple parties to perform collaborative analytics while ensuring each party only has access to the data they own.
“Traditional approaches for protecting data and managing data privacy leave data exposed and at risk when being processed by applications, analytics, and machine learning (ML) models,” said Rishabh Poddar, Co-founder & CEO, Opaque Systems. “The Opaque Confidential AI and Analytics Platform solves this challenge by enabling data scientists and analysts to perform scalable, secure analytics and machine learning directly on encrypted data within enclaves to unlock Confidential Computing use cases.”
SOURCE: PR Newswire