Data security firm Fortanix Inc. and tech giant NVIDIA have collaborated on a cutting-edge platform designed to facilitate the deployment of secure AI solutions within organizations’ data centers or sovereign environments. This innovative solution, powered by NVIDIA’s confidential computing GPUs, aims to establish trust and security throughout the entire AI process, especially in industries such as healthcare, finance, and government with stringent privacy and regulatory demands.
Fortanix’s CEO, Anand Kashyap, emphasized the significance of ensuring trust and security in AI operations by securing every layer, from the chip to the model to the data. This joint solution addresses the critical need for trustworthy AI implementation in sectors constrained by strict privacy and regulatory requirements, offering a turnkey platform that enables organizations to leverage AI with confidence, even when dealing with sensitive or regulated information.
The collaboration between Fortanix and NVIDIA comes at a crucial moment for industries seeking to harness the power of AI while maintaining compliance with privacy and regulatory standards. By utilizing NVIDIA’s confidential computing GPUs, Fortanix’s platform enables enterprises to build and run AI systems on sensitive data without compromising security or control.
The core of the Fortanix-NVIDIA partnership lies in a confidential AI pipeline that ensures the protection of data, models, and workflows throughout their lifecycle. By integrating Fortanix’s Data Security Manager and Confidential Computing Manager with NVIDIA’s GPU architecture, the platform enforces strict access controls and verifies the trustworthiness of AI workloads and infrastructure using composite attestation.
This innovative approach provides a provable chain of trust from the hardware chip to the application layer, catering to industries where confidentiality and compliance are paramount. The platform enables enterprises to move from pilot projects to production-ready AI systems quickly and securely, with minimal reconfiguration required for existing AI workloads migrating to NVIDIA’s Hopper or Blackwell GPU architectures.
In addition to enhancing security and trust in AI operations, the joint platform addresses compliance requirements by enforcing role-based access control, detailed audit logging, and secure key custody. This focus on compliance and sovereignty makes the solution ideal for industries such as banking, healthcare, and government contracting that must adhere to stringent data protection regulations.
Furthermore, Fortanix’s platform is future-proofed for the post-quantum era, supporting post-quantum cryptography within its Data Security Manager product. This forward-looking approach ensures that enterprises are prepared for the evolving landscape of secure computing frameworks as quantum computing research advances.
While designed for on-premises and sovereign use cases, the platform also offers flexibility for running in major cloud environments that support confidential computing. Enterprises operating across multiple regions can maintain consistent key management and encryption controls, allowing them to shift AI workloads between data centers or cloud regions without compromising data security.
Fortanix’s partnership with NVIDIA represents a significant step forward in securing AI workloads and ensuring trust in AI operations, particularly in highly regulated environments. The joint platform will be showcased at NVIDIA GTC, offering live demonstrations and discussions on securing AI workloads in industries where confidentiality and compliance are non-negotiable.
Fortanix Inc. was founded in 2016 by Anand Kashyap and Ambuj Kumar, former Intel engineers with extensive experience in trusted execution and encryption technologies. Today, Fortanix is a global leader in confidential computing and data security, offering solutions that protect data across its lifecycle, from storage and transmission to active use. The company’s focus on securing AI workloads reflects its commitment to bridging the gap between research-grade cryptography and enterprise adoption, catering to industries with sensitive or regulated data requirements.
