- Opaque Systems Inc., a firm specializing in secure data analytics, has introduced a new platform that will include the most recent advancements in confidential artificial intelligence and analytics.
- The platform accelerates confidential computing use cases by enabling data scientists to harness their existing SQL and Python expertise while working with confidential data to execute analytics and machine learning.
Secure data analytics startup Opaque Systems Inc. released a new platform that, according to the company, incorporates the most recent developments in confidential artificial intelligence and analytics.
The Opaque platform has been developed to unlock use cases in confidential computing, enabling data scientists to execute safe and collaborative analysis directly on encrypted data. The platform accelerates confidential computing use cases by allowing data scientists to harness their existing SQL and Python expertise while working with confidential data to execute analytics and machine learning.
Through the platform, data scientists may overcome the data analytics constraints inherent in TEEs due to their stringent access and usage restrictions.
Using TEEs or enclaves that encrypt data during processing, separating it from access, exposure and dangers, confidential computing provides the solution. However, Opaque Systems argue that TEEs have historically presented difficulties for data scientists because of restricted data access, lack of tools that enable data sharing and collaborative analytics, and the necessity for highly specialized expertise to work with TEE-encrypted data.
The Opaque Platform solves the difficulties inherent in processing enclaved data by offering multi-party confidential analytics and AI solution that enables frictionless analytics to be performed on encrypted data within TEEs. Additionally, the platform provides secure data exchange and enables many parties to conduct collaborative analytics while guaranteeing that each party has exclusive access to the data they own and control.
Rishabh Poddar, the Co-founder and Chief Executive Officer of Opaque Systems, said, “Traditional approaches for protecting data and managing data privacy leave data exposed and at risk when processed by applications, analytics and machine learning models. 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.”
The Opaque Confidential AI and Analytics Platform ensures that code and data within enclaves are unavailable to other users or processes co-located on the system. Organizations may encrypt their confidential data on-premises, speed the transition of sensitive workloads to enclaves in confidential computing clouds, and analyze encrypted data while assuring it is never unencrypted during the computation’s lifespan.
Key capabilities include safe data sharing and privacy, enabling teams to communicate TEE-protected data securely while complying with regulatory and compliance requirements. With powerful encryption and secure hardware enclave technology – data security throughout the lifespan ensures that all sensitive data, including personally identifiable information, is secured.
Security, policy enforcement and governance employ many layers of security, such as Intel Software Guard Extensions, secure enclaves, sophisticated cryptography, and policy enforcement, to offer defense in depth, guaranteeing code and data integrity and side-channel attack protection.
In June, Opaque Systems was in the headlines for raising $ 22 million in additional investments. Walden Catalyst Management, Storm Ventures, Thomvest Ventures, Intel Capital, Race Capital, The House Fund, and Factory HQ Fund were among the company’s investors.