Follow Datanami:
June 6, 2024

Opaque Launches New Platform For Running AI Workloads on Encrypted Data


While enterprises understand the need to innovate to stay competitive, they are also cautious about protecting their data. Enterprises often grapple with balancing innovation and security when it comes to extracting value from their data using generative AI.

Existing techniques to operationalize the data are either too risky or inadequate. As a result, most organizations are forced to be cautious and prioritize security, resulting in stalled AI projects. 

Opaque Systems, a security data analytics startup, offers a solution to overcome these challenges and unlock the full value of organizations’ data. The company has unveiled its new Confidential AI platform, designed to accelerate AI workloads into production.

The new platform was announced at the 2024 Confidential Computing Summit in San Francisco, CA. One of the key capabilities of the new platform is that it enables enterprises to run a wide range of AI workloads, such as SWL analytics and AI inference, on encrypted data without needing any reengineering. It also supports machine learning pipelines and popular languages and frameworks for AI, including Spark and Python. 

The Confidential AI platform was developed at the Berkeley RISELab, a world-renowned lab known for developing technologies such as Apache Spark and Databricks. It was at this lab where the breakthrough MC2 (Multiparty Collaboration and Competition) platform was created, incubated, and open-sourced. In 2021, this platform served as the foundation to build the Opaque platform. 

Building on Opaque’s existing services that facilitate secure collaboration with cryptographic verification of privacy, the new platform allows organizations to unlock business insights securely and efficiently from sensitive data that wasn’t fully utilized before.

Last year, Opaque announced key innovations to the platform including broader support for confidential AI use cases and new safeguards for ML and AI models from exposure to unauthorized parties. 

“Opaque offers a breakthrough for organizations struggling with the tension between innovation and security. By embedding privacy and security into every step of the ML pipeline, we enable enterprises to accelerate AI adoption confidently,” said Chester Leung, co-founder and Head of Platform Architecture at Opaque. 

“Our confidential AI platform uniquely enables the processing of encrypted data without a noticeable performance hit at cloud scale. With Opaque securing entire data workloads, companies can unlock new business opportunities and manage risks effectively, all while maintaining absolute control and privacy of their data.” 

Use cases for the new platform span across various industries. In the high-tech sector, Confidential AI can be used to secure data pipelines for analytics and ML workloads and enable dynamic model training on encrypted data.  

Users in the manufacturing sector can use the platform as a confidential control plane to enforce data governance rules. Financial services can also benefit from the platform through secure data sharing and collaboration across business units. 

Human resources professionals can harness the power of the platform to securely share and analyze employee data across multiple data silos and ensure enterprise compliance with data privacy regulations. 

With the launch of the new platform,  enterprises could finally have a solution to eliminate the tradeoff between innovation and security. As more organizations use the new platform, we will have a better understanding of the performance of Confidential AI in terms of integration with existing ecosystems and scalability.

Related Items 

VAST Data Partners with Superna to Enhance Cybersecurity for AI Workloads

Cisco Announces Nexus HyperFabric AI Clusters with NVIDIA for Enhanced AI Workloads

Immuta’s New Integration with Databricks Provides Security at Scale for Data and AI Workloads