Fortanix Confidential AI Protects Proprietary Model IP and Data for Secure AI Inference in Enterprise AI Factories.

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Fortanix Confidential AI for AI Labs 

Expand
Your Markets While
Keeping Your
IP Protected

Run your models wherever enterprise customer data resides, with cryptographic assurance that your IP stays secured, every step of the way. 

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Protect Your AI IP with
Hardware-Based Proof 

Many enterprises must meet stringent data residency and compliance mandates, pushing AI labs to deploy frontier models directly where that sensitive data lives. Fortanix Confidential AI, built jointly with NVIDIA on Confidential Computing, turns that requirement into opportunity, enabling secure deployment in third-party environments with verifiable assurance that model weights stay protected from the underlying infrastructure, OS, and even privileged administrators. AI labs now can accelerate revenue growth while keeping their model IP completely protected.  

hardware based proof

Benefits

union
Unlock New Revenue Streams   
Unlock New Revenue Streams   

Unlock regulated markets, support sovereign AI initiatives, and deliver low-latency, real-time performance.  

Encrypt
Scale Deployments Without Exposure  

Package model weights inside an encrypted, attested CVM image once and deploy to any number of enterprises.  

trust
Gain Trust Through Verification   

 Offer verifiable, auditable proof of AI workload protection.    

Resources

Here are some of latest news, blogs, resources, events, and more

ai model owners

Solution Brief

Fortanix Confidential AI for AI Model Owners
Enabling Secure Enterprise Voice AI While Protecting Proprietary Models and Sensitive Data

Case Study

Enabling Secure Enterprise Voice AI While Protecting Proprietary Models and Sensitive Data
cai whitepaper

Whitepaper

Building Confidential Inference Systems: Securely Deploy Frontier Models On-Prem and Protect Enterprise Data
Get an inside look at how some of today’s most innovative companies use GenAI securely in Fortanix. 
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As of January 2026

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