Fortanix Confidential AI Protects Proprietary Model IP and Data for Secure AI Inference in Enterprise AI Factories
Fortanix has announced a new Confidential AI solution powered by NVIDIA Confidential Computing that enables enterprises to run third-party proprietary AI models on their most sensitive data — without exposing either. The solution gives model owners like ElevenLabs cryptographic guarantees that their IP remains protected, while enterprises in regulated industries such as government, healthcare, and finance can run AI inference on their own servers without violating data privacy obligations.
Fortanix Eliminates Single-Source Entropy Compliance Risk with Multi-Sourced Quantum Randomness for Enterprise Key Generation
Fortanix has announced a new multi-sourced quantum entropy capability within Fortanix Data Security Manager (DSM), enabling enterprises to diversify encryption key generation at the origin of trust. Through partnerships with Qrypt and Quantum Dice, Fortanix now integrates independent, physics-based quantum entropy sources directly into its key management workflows, eliminating single points of failure at the root of key generation and extending zero-trust principles to the entropy layer.
Fortanix Wins Big at the 2026 Global InfoSec Awards
Fortanix has been named a winner in the 14th Annual Global InfoSec Awards by Cyber Defense Magazine, announced during the RSAC Conference 2026. Selected from over 3,000 global entries by certified security experts, the recognition highlights Fortanix's innovation in Confidential AI and Data Security, validating its "Data-First" approach to protecting sensitive data and AI models at rest, in motion, and in use.
Fortanix Named Amongst ‘Best Startup Employers 2026’ by Forbes
Deploy Frontier AI Where Data Lives
Securely distribute AI models where enterprise data is and keep both model IP and sensitive data fully protected with Confidential Computing.
Why AI Factories Are Replacing General-Purpose Clouds For Important AI Workloads
Why Confidential Computing is the missing link for LLMs in E-commerce Risk Detection
Architecture Decisions That Matter for the Next 12 Months for the AI Factory Tech Stack
Why Traditional Security Is Failing Sensitive AI Workloads and Why Confidential Computing Is Now Required
Open vs. Closed Weight Models and Why You Need Confidential Inference Either Way
An AI Factory is Not a GPU Cluster and Securing Only One Layer is a Dangerous Illusion
Things You Must Protect in AI Systems: Model Weights, Prompts & Context
